Journal articles on the topic 'Investment analysis Computer simulation'
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Demirci, Emrullah. "Simulation Modelling and Analysis of a Port Investment." SIMULATION 79, no. 2 (February 2003): 94–105. http://dx.doi.org/10.1177/0037549703254523.
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Kovbasiuk, Kateryna, Kamil Židek, Michal Balog, and Liudmyla Dobrovolska. "ANALYSIS OF THE SELECTED SIMULATION SOFTWARE PACKAGES: A STUDY." Acta Tecnología 7, no. 4 (December 31, 2021): 111–20. http://dx.doi.org/10.22306/atec.v7i4.120.
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The simulation software market is becoming more complex and universal. Computer simulations are thus more accessible and are becoming a modern tool that has a wide application in industry. Their potential and benefits can be used in small and large projects. A simulation model can take into account inventory, assembly, production and human resources, leading to decisions that can maintain or improve efficiency at the lowest possible cost. The data obtained through the simulation allow to test different combinations and scenarios in the virtual world. The benefits of manufacturing simulation include reducing investment risk, minimizing waste, improving efficiency, reducing energy consumption and even increasing worker health. The question arises as to which of the possible simulation packages is the most suitable for a given company, so that the investments made are the best possible. In the first part of the paper the theoretical basis of simulation in Industry 4.0 is presented, including the description of the possible simulation modelling tools. The second part of the paper offers comparative and descriptive analysis of six selected discrete-event simulation software packages – AnyLogic, Arena, FlexSim, SIMUL8, Tecnomatix Plant Simulation and WITNESS. The given simulation tools are compared based on their main characteristics, simulation features, application areas and popularity among the companies which use simulation software packages.
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Wang, Zhong, Yingying Zhang, Lian Lian, and Chenglong Chu. "Evaluating transportation infrastructure investment on a regional level: a system dynamics simulation." SIMULATION 94, no. 10 (January 22, 2018): 943–54. http://dx.doi.org/10.1177/0037549717746750.
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Transportation infrastructure investment (TII) has significant influence on regional economic development. This paper aims to measure the potential economic impact of TII and to help policymakers to evaluate different alternatives and strategies at the regional level through a system dynamics (SD) approach. First, an SD model is established to simulate the impact of TII on the economy and employment. The relationship between transportation investments and economic development is examined and the relevant employment and economic indicators are identified. Second, the variables, flow diagrams, and structural equations of the SD model are defined. Third, the program Vensim is employed to establish the SD model with economy, transportation, and employment subsystems. It is then calibrated based on the historical statistics data in Liaoning Province, China. Finally, scenario analysis of different transportation investment plans is presented. The results will help investors, policymakers, and government agencies to estimate the potential outcomes of proposed transportation investment plans and to further develop optimal policies for transportation investment.
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Guodong Chen. "Based on Monte Carlo Simulation Investment Portfolio VaR Risk Analysis." Journal of Convergence Information Technology 8, no. 9 (May 15, 2013): 1071–79. http://dx.doi.org/10.4156/jcit.vol8.issue9.130.
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Gan, Juan, and Chunxi Wang. "The Investment Model of Aviation Industry VCGF Based on AHP Analysis of Computer Simulation." Journal of Physics: Conference Series 1578 (July 2020): 012081. http://dx.doi.org/10.1088/1742-6596/1578/1/012081.
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He, Bo, Dong Hong Wang, Fei Li, and Bao De Sun. "Simulation Study on Wax Injection for Investment Casting." Advanced Materials Research 834-836 (October 2013): 1575–79. http://dx.doi.org/10.4028/www.scientific.net/amr.834-836.1575.
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As investment castings grow in size and complexity, control of wax pattern dimensions becomes increasingly important and difficult. Conventionally, mold design and dimensions are re-worked by trial-and-error procedures until casting dimensions are produced within acceptable dimensional tolerances, increasing the cost of the castings.Nowadays, numerical simulation is an efficient tool for mold design. However, one of the critical difficulties in using computer models for the simulation of wax injection process is the lack of material properties of the wax. Material property measurements were conducted in this study that can be used as input in Moldflow. Then, 3D numerical simulation could be applied in analysis with mold design of thin-walled wax pattern, with high dependability. Simulation results of filling time and the location of the air traps were analyzed. Consequently, best gate location and reasonable gate system were determined. The paper highlighted the effectiveness of simulation in filling optimization and deformation of wax pattern.
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Smith, Leighton L. "High Technology and Manufacturing: Work Physiology Improvements via the Ergonomic Simulation Analysis System." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 38, no. 10 (October 1994): 664–67. http://dx.doi.org/10.1177/154193129403801027.
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This article describes an ergonomic analysis tool called the Ergonomic Simulation Analysis System (ESAS). This system is used in conjunction with computer graphic simulation software. The ESAS integrates work physiology ergonomic models and indexes with manufacturing workplace simulation. It enables engineers and analysts to extract from the simulation sequences robust and meaningful ergonomic analyses in lifting and in repetitive motion activities. The system is simple to operate, allows analysts to execute its functions in a seamless manner when using other software, provides robust results with very little setup time investment, and provides effective and readily assimilated visual products of candidate workplace designs and work methods.
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Botchkarev, Alexei. "Estimating the Accuracy of the Return on Investment (ROI) Performance Evaluations." Interdisciplinary Journal of Information, Knowledge, and Management 10 (2015): 217–33. http://dx.doi.org/10.28945/2338.
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Return on Investment (ROI) is one of the most popular performance measurement and evaluation metrics. ROI analysis (when applied correctly) is a powerful tool in comparing solutions and making informed decisions on the acquisitions of information systems. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of information systems implementations. Measurements theory and error analysis, specifically propagation of uncertainties methods, were used to derive analytical expressions for ROI errors. Monte Carlo simulation methodology was used to design and deliver a quantitative experiment to model costs and returns estimating errors and calculate ROI accuracies. Spreadsheet simulation (Microsoft Excel spreadsheets enhanced with Visual Basic for Applications) was used to implement Monte Carlo simulations. The main contribution of the study is that this is the first systematic effort to evaluate ROI accuracy. Analytical expressions have been derived for estimating errors of the ROI evaluations. Results of the Monte Carlo simulation will help practitioners in making informed decisions based on explicitly stated factors influencing the ROI uncertainties.
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Lu, Jing Jing, and Xuan Xi Ning. "Application of Monto-Carlo Method in HR Investment Risk Evaluation." Key Engineering Materials 458 (December 2010): 131–36. http://dx.doi.org/10.4028/www.scientific.net/kem.458.131.
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Monto-Carlo method is widely used for project risk analysis. Evaluating the risk in HR (Human Resources) investment project, which is of hi-investment and hi-return, by Monto-carlo method is a new attempt. In this paper, by taking cost, profit and risk in the HR investment as index, emulation model of HR investment and index function of risk evaluation were established. Simulation about the whole investment course was done by computer program using Monto-Carlo method. Case study of HR investment risk evaluation was done later using concrete data.
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NI, JINLAN, and DEEPAK KHAZANCHI. "INFORMATION TECHNOLOGY INVESTMENT DECISIONS UNDER ASYMMETRIC INFORMATION: A MODIFIED RATIONAL EXPECTATION MODEL." International Journal of Information Technology & Decision Making 08, no. 01 (March 2009): 55–72. http://dx.doi.org/10.1142/s0219622009003260.
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In this paper, we propose that information technology (IT) managers make investment decisions about new IT initiatives based on a modified rational expectation model. Unlike traditional rational expectation models, we emphasize the relevance of market uncertainty and its impact on the return of new IT investment. This results in information acquisition decisions by managers that can cause information asymmetry. This information asymmetry is endogenous and so the IT manager can become well informed if and only if it is beneficial to do so. We also capture different levels of IT investment across managers by introducing heterogeneity across managers in terms of different levels of initial capital. Based on a simulation analysis to validate our theoretical model, we find that it is the IT manager with larger initial capital outlay who is particularly interested in acquiring information about their IT investments in order to reduce any asymmetry with competitors. Furthermore, we find that holding other things constant, fewer IT investors are informed when information cost increases and in consequence the difference of investment level between the informed and uninformed investors is more pronounced.
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Lyubchenko, M. A., Martinez Juan Marcos Garcia, Quintana Laura Angelica Samora, and V. S. Syromyatnikov. "Computer Simulation of the Press Fit Connection." Proceedings of Higher Educational Institutions. Маchine Building, no. 4 (733) (April 2021): 3–11. http://dx.doi.org/10.18698/0536-1044-2021-4-3-11.
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The design of modern technology is associated with increased requirements for strength and manufacturability. Press fit connections of small size parts can withstand significant workloads, so they are widely used in mechanisms and machines. Traditionally, the calculation of press fit connections is performed according to classical formulas using a large amount of reference data. The calculations use standard recommendations that make it easier to obtain solutions with a minimum investment of time. However, the time saving limits the search to a few joints, which are not always the best in some indicators. Modeling press fit joints with different combinations of parameters leads to the formation of hundreds of potential joints. To check their performance, it is necessary to use modern computing facilities. The computer has almost unlimited possibilities for computing speed and storing arrays of information. Simulation of press fit connections on a computer allows obtaining regression metamodels, accessing the statistical significance of parameters, and determining the area of workable connections. It becomes possible to optimize the design of the joint in terms of strength, weight and assembly technology. The system for calculating and statistical analysis of press fit connections has been developed on the basis of existing standards. A program has been developed providing the joints formation and verification with an assessment of their suitability for the specified requirements.
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Tutor Roca, Santiago José, Javier Pernas Álvarez, Inés Taracido López, and Adolfo Lamas Rodríguez. "Discrete event simulation for the investment analysis of offshore wind manufacturing processes." International Journal of Simulation and Process Modelling 1, no. 1 (2021): 1. http://dx.doi.org/10.1504/ijspm.2021.10044416.
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Rodríguez, Adolfo Lamas, Inés Taracido López, Javier Pernas Álvarez, and Santiago José Tutor Roca. "Discrete event simulation for the investment analysis of offshore wind manufacturing processes." International Journal of Simulation and Process Modelling 17, no. 2/3 (2021): 137. http://dx.doi.org/10.1504/ijspm.2021.121706.
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MOON, GISUNG, and LOUIS A. LeBLANC. "The Risk Adjustment of Required Rate of Return for Supply Chain Infrastructure Investments." Transportation Journal 47, no. 1 (January 1, 2008): 5–16. http://dx.doi.org/10.5325/transportationj.47.1.0005.
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Abstract The purpose of this article is to apply a risk-adjusted required rate of return to evaluate supply chain capital investments. As part of the design methodology, a computer simulation provides expected cash flows resulting from alternative supply chain investments. These cash flows are discounted at a risk-adjusted required rate of return. The analysis represents a process to measure the risk inherent in supply chain investments. The logistics and supply chain literature has not addressed this problem of the risk inherent in a specific supply chain project. A corporate-wide hurdle rate applied to usually conservative supply chain investments may result in less than adequate investments in supply chain infrastructure. Prior studies have determined risk-adjusted required rate of return for the entire firm, an enterprise's entire supply chain network, but not an individual project within the supply chain. This study calculates a required rate of return for a specific supply chain investment project using a discrete simulation model rather than the more common mathematical model. Individual supply chain investment projects may have less risk or possibly more risk than reflected by a corporate hurdle rate or a supply chain hurdle rate. Using a standard required rate of return could result in too little or too much investment in supply chain facilities. In this study, when the risk-adjusted rate was employed to discount expected cash flows, only two of eleven alternatives evaluated were acceptable investments. The best investment with the highest return was a 12 percent increase in ship loading rate combined with a 33 percent increase in rail unloading capacity. It provided a benefit-cost ratio of 1.25. The limited availability of publicly traded firms that invest in supply chain projects represents a constraint, limiting the accuracy of estimating the market risk factor. Nevertheless, the practical implication is that, when making supply chain infrastructure investment decisions, it is advisable to adjust risk factors in evaluating such capital investments. This approach is preferable to using a corporate-wide hurdle rate, typically too high for such conservative investments. A firm-wide hurdle rate might result in under investment in supply chain facilities.
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Taufik, Shamsuddin Sulaiman, T. A. Abdullah, and Sivarao. "Design and Simulation on Compressor Metal Matrix Composite by Investment Casting." Advanced Materials Research 264-265 (June 2011): 403–8. http://dx.doi.org/10.4028/www.scientific.net/amr.264-265.403.
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Compressor is a part of turbocharger approaches that utilize the exhaust gas of an automobile to drive the compression device. The purpose of turbocharging is to increase the intake pressure and the amount of air into the combustion chamber to improve the efficiency of the engine. Compressor impeller determines the service life of the turbocharger. This paper proposes the new methodology of producing the compressor impeller using Metal Matrix Composite (MMC) material by investment casting. In general, this study presents the tasks pertaining to metal matrix composites and their interactions in designing of compressor impeller. This study presents the use of genetic algorithm (GA) and computer programs for designing a new compressor and determined the wax pattern dimensions based on three-dimensional finite-element simulations as a preliminary study by using investment casting method. The model of thermal and mechanical analysis was developed by ANSYS. As the results, the simulation model was generated and it could be used for improving the design of turbine-compressor assembly through the bottom geometry changes of the compressor.
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Rotela Junior, Paulo, Eugenio Fischetti, Victor G. Araújo, Rogério S. Peruchi, Giancarlo Aquila, Luiz Célio S. Rocha, and Liviam S. Lacerda. "Wind Power Economic Feasibility under Uncertainty and the Application of ANN in Sensitivity Analysis." Energies 12, no. 12 (June 14, 2019): 2281. http://dx.doi.org/10.3390/en12122281.
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Wind power has grown popular in past recent years due to environmental issues and the search for alternative energy sources. Thus, the viability for wind power generation projects must be studied in order to attend to the environmental concerns and still be attractive and profitable. Therefore, this article aims to perform a sensitive analysis in order to identify the variables that influence most in the viability of a wind power investment for small size companies in the Brazilian northeast. For this, a stochastic analysis of viability through Monte Carlo Simulation (MCS) will be made and afterwards, Artificial Neural Networks (ANN) models will be applied for the most relevant variables identification. Through the sensitivity, it appears that the most relevant factors in the analysis are the speed of wind, energy tariff and the investment amount. Thus, the viability of the investment is straightly tied to the region where the wind turbine is installed, and the government incentives may allow decreasing in the investment amount for wind power. Based on this, incentives programs for the production of clean energy include cheaper purchase of wind turbines, lower taxing and financing rates, can make wind power more profitable and attractive.
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Suh, Sunduck, Wonho Suh, and Jung In Kim. "Risk analysis model for regional railroad investment." Engineering Computations 34, no. 1 (March 6, 2017): 164–73. http://dx.doi.org/10.1108/ec-10-2015-0323.
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Purpose The purpose of this study is to model risks in financial analysis. These risks associated with uncertainties in the projects should be properly addressed to ensure proper decision regarding the projects. Performance indicators should be developed and assessing risks has high priority. All these activities comprise appraisal, and based on these, a proper course of action should be recommended. Design/methodology/approach To analyze the attractiveness of a project for foreign regional railroad investment or participation, the project should be analyzed in a systematic way. First, the project’s goals and objectives should be evaluated for compatibility. Also, criteria of acceptability for stakeholders should be checked against output from the project. Usually, a project can have many alternatives, and impacts of each alternative should be analyzed in terms of quantitative and qualitative forecasts of impacts. Benefits and costs need to be counted in proper units of measurement per goals and objectives. Findings This paper shows that risk modeling can reflect uncertainty in decision-making and provide robustness of modeling process and improved communication. Also, challenges are presented in using risk analysis. Originality/value To overcome the shortcomings of traditional mathematical optimization model in identifying best sets of projects for private application, the proposed model finds ways to incorporate risk management components for the optimization procedure. Based on simulation results, a brute force solution procedure using enumeration can be used. Another approach is recommended to use the genetic algorithm process to reduce the number of alternatives to search to reach an optimal solution.
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Ghisi, E., L. P. Thives, and R. F. W. Paes. "Investment feasibility analysis of rainwater harvesting in a building in Brazil." Water Supply 18, no. 4 (November 7, 2017): 1497–504. http://dx.doi.org/10.2166/ws.2017.218.
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Abstract The objective of this study is to assess the investment feasibility analysis of rainwater harvesting in a building located in Brazil. Rainwater was used to supply toilets, cleaning and irrigation. The costs of materials, labour and maintenance were obtained to carry out the economic analysis; the indicators used were the net present value, internal rate of return and payback period. The investment feasibility analysis and the potential for potable water savings were obtained by means of computer simulation. The potential for potable water savings ranged from 26.70% to 64.70%. The net present value, internal rate of return and payback period for the best scenario were, respectively, R$132,801.47, 3.73% per month and 32 months. For the worst scenario the net present value was R$9,451.26, the internal rate of return was 0.91% per month and the payback period was 166 months. Thus, rainwater can be used as a sustainable alternative and be financially feasible.
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Frondelius, Tero, Hannu Tienhaara, and Mauri Haataja. "History of structural analysis & dynamics of Wärtsilä medium speed engines." Rakenteiden Mekaniikka 51, no. 2 (December 8, 2018): 1–31. http://dx.doi.org/10.23998/rm.69735.
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This paper opens up the history of structural analysis and dynamics simulations of Wärtsilä engines. It cites already published articles and theses with some backgrounds information. It also discusses some of the backgrounds of the in-house tool development. Additionally, this paper presents the development of the computers and investment of the simulation capacity in order to understand how it has been the enabler of ever more complicated models. It lists the work done during fifty decades. The authors sincerely attempt to make this article as reader-friendly as possible, even though there are over 220 references, which of course demonstrates how dedicated Wärtsilä has been in supporting numerical simulations research in the past fivedecades.
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Taufik, Shamsuddin Sulaiman, T. A. Abdullah, and Sivarao. "Design and Simulation on Cast Metal Matrix Composite by Investment Casting." Advanced Materials Research 264-265 (June 2011): 323–28. http://dx.doi.org/10.4028/www.scientific.net/amr.264-265.323.
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Metal Matrix Composite (MMC) is produced normally by melting the matrix material in a vessel and the molten metal is stirred systematically to form a vortex, and then the reinforcement particles are introduced through the side of vortex formed. However, this approach has disadvantages, mainly arising from the particle addition and the stirring method. There is certainly local solidification of the melt induced by the particles during particle addition. This condition increases the viscosity of the slurry and appears as air pockets between the particles. Moreover, the rate of particle addition needs to be slowed down particularly when the volume fraction of the particles to used increases. This study proposes the new methodology of producing cast MMC by investment casting. Deformations of the die-wax and shell alloy systems are considered in a coupled manner, but the coupled deformation of the wax-shell system is not included. Therefore, this study presents the tasks pertaining to metal matrix composites and their interactions. As a result, the work on wax and wax-die interactions is discussed. This study presents the use of computer programs for determining the wax pattern dimensions based on three-dimensional finite-element simulations. The model for coupled thermal and mechanical analysis is developed by ProCAST. The wax model is described. The following factors are considered in the analysis: (1) the restraint due to geometrical features in the metal die; and (2) process parameters such as dwell time, die/platen temperature, injection pressure, and injection temperature.
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Yu, Zhen Xi. "Non-Linear Three-Dimensional Finite Element Analysis of Some Extremely Deep Foundation Pit Support." Applied Mechanics and Materials 443 (October 2013): 79–83. http://dx.doi.org/10.4028/www.scientific.net/amm.443.79.
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In recent years, with the enhancement of overall national strength in China, the computer simulation technology has been developed rapidly and widely applied to engineering construction. Particularly, investment proportion of the technology in deep foundation pit engineering is immense. Yet affected by national conditions in China, the construction and application of deep foundation pit engineering have many extensive factors. It also results in insufficient vigor of finite element analysis of deep foundation pit support construction. In this way, construction problems arise frequently under the condition that there exist buildings around. With some deep foundation pit support engineering, the thesis conducts simulation analysis of the engineering through the technology of nonlinear three-dimensional finite element.Project profile
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Lu, Hongbo, and Lifeng Wang. "Risk Analysis of Enterprises’ Investment in Infrastructure in Developing Countries Based on Structural Equation Model." Mobile Information Systems 2022 (April 30, 2022): 1–7. http://dx.doi.org/10.1155/2022/4790726.
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In order to control the risks of Chinese enterprises in infrastructure investment in developing countries, the corresponding evaluation system is constructed through a structural equation model algorithm to analyze these risks, so as to achieve risk prediction and risk controllability. Structural equation modeling is a method to establish, estimate, and test causality. It can replace multiple regression, path analysis, factor analysis, covariance analysis, and other methods and clearly analyze the effect of individual indicators on the population and the interrelationship between individual indicators. It is a multivariate statistical modeling technology mainly applied to confirmatory model analysis. Due to the guidance of national policies, there are more and more opportunities for Chinese enterprises to invest abroad. However, due to the influence of political, economic, and environmental factors, overseas investment is facing many difficulties. This paper analyzes the risks from four aspects: bilateral policy risk, legal difference and litigation risk, international economic risk, and technical risk through structural equation model algorithm. Aiming at these risks, the simulation software of the algorithm is constructed in MATLAB big data analysis software, and the risk control measures are put forward. Finally, with the support of China’s policies, in order to ensure the investment income, we should carry out risk intervention for the foreseeable risk and reduce the impact of risk on the investment income as much as possible, so as to improve the risk prevention and management awareness of overseas investment business. By analyzing the characteristics of venture capital and the various kinds of risks affecting venture capital, the risk structure model estimation of risk sneak attack is established by using the principle of structural equation model, and the impact of various risks on investment risks can be analyzed, so that the risk measurement and control of venture capital provides the basis of theoretical knowledge.
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Reisinger, Thomas W. "A Simulation-Based Approach to Evaluating Commercial Thinning Decisions in Loblolly Pine Plantations." Southern Journal of Applied Forestry 9, no. 4 (November 1, 1985): 211–16. http://dx.doi.org/10.1093/sjaf/9.4.211.
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Abstract Computer simulation techniques are described which evaluate the impact of various stand conditions, management regimes, harvesting systems, and future market scenarios on current thinning decisions in pine plantations. Four simulation programs (PTAEDAR, PTAEDA, GENMAC, and HSS) were linked to predict tree growth/stand development and to model mechanized thinnings and final harvests. Simulation results were then combined with an investment analysis program to calculate the net present value of each strategy. An example analysis for a "typical" loblolly pine (Pinus taeda) plantation is presented. As described here, simulation is a practical method of evaluating the profitability of a wide range of alternatives, including planting spacings, thinning regimes, and rotation ages for managing future plantations of loblolly pine.
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Pang, Sulin, Chao Deng, and Susong Chen. "System Dynamics Models of Online Lending Platform Based on Vensim Simulation Technology and Analysis of Interest Rate Evolution Trend." Computational Intelligence and Neuroscience 2022 (August 9, 2022): 1–21. http://dx.doi.org/10.1155/2022/9776138.
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This paper mainly focuses on the construction of a system dynamics model of an online lending platform and the application of Vensim simulation technology in the analysis of the evolution trend of the investment interest rate. The system dynamics flow graph models of the investment subsystem, loan subsystem, and interest rate subsystem of the online lending platform were innovatively constructed; the level variable, flow rate variable, auxiliary variable, and mathematical relations between these variables as they relate to the platform were innovatively studied. Based on the key variables of the online lending platform, a system dynamics model of the online lending platform was innovatively constructed. The parameters were assigned using data from China’s online lending industry, and the logical consistency, sensitivity, and validity of the simulation data of the system dynamics model were tested. Finally, we used Vensim simulation technology to simulate and analyze the impact of emergency scenarios on the interest rate evolution trend. Overall, this paper provides a scientific simulation technology and data analysis method for examining online lending platforms.
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Zhang, Yang You. "Target Searching Simulation of Computer Information Technology Based on Improved Apriori Algorithm." Applied Mechanics and Materials 608-609 (October 2014): 631–35. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.631.
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The fixed assets of large enterprises are the material basis for the development of enterprises, and the innovation of financial management has great significance to the economic growth efficiency of enterprises. Only by improving the using efficiency of fixed assets and reducing the production cost, it can improve the competitiveness of large enterprises. In this paper we use the AprioriTidStr algorithm to improve the Apriori algorithm, and use VB software to establish financial management index table of fixed assets. According to the index table, we establish the search association rule knowledge base of financial management target. In order to test the stability and reliability of the system, we do numerical analysis on the fixed assets investment of enterprises, and obtain the financial forecast accurate rate curve and the financial control form within one week. It provides the computer technology support for innovation of large fixed assets management.
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Alhabeeb, M. J. "Comparative Analysis of the Traditional Models for Capital Budgeting." International Journal of Marketing Studies 8, no. 6 (November 11, 2016): 16. http://dx.doi.org/10.5539/ijms.v8n6p16.
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<p>Financial decision making for investing firms requires metric tools for comparison and analysis. The managerial choice among many investment alternatives with complex possibilities has made it easier to rely on the now more advanced computer programs of simulation that considers the uncertainty and stochastic changes in the cash flow and risk levels. The major drawback here, especially in the academic world, is the increasing dependency on software and departing from the underlying mathematical reasoning that is most practically fathomed by the manual problem solving. This paper goes back to the tradition on analyzing and comparing the major models of capital budgeting.</p>
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El-Khalil, Raed. "Simulation analysis for managing and improving productivity." Journal of Manufacturing Technology Management 26, no. 1 (February 2, 2015): 36–56. http://dx.doi.org/10.1108/jmtm-03-2013-0024.
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Purpose – The current economic crisis increased the demand on management to improve process efficiency. The purpose of this paper is to identify and resolve inefficiencies within the car assembly system utilizing discrete simulation modeling and analysis in order to improve productivity at one of the original equipment manufacturers (OEM) body shops in North America. Design/methodology/approach – This research was driven by a manager’s recommendation from one of the Big Three (GM, Ford, Chrysler LLC) companies in order to improve operational performance. The data utilized in creating the simulation model was obtained from one of the assembly facilities that produce three different vehicles over a period of one year. All model simulation, inputs and outputs were discussed and agreed upon by facility management. Findings – The established base model was verified and validated to mimic the actual facility outputs indicating all process bottlenecks. Two model scenarios were considered: the first scenario focussed on the top bottleneck processes flexibility with a ROI of 497 percent, while the second considered changing the model mix percentage leading to a cost improvement of $1.6 million/annually. Research limitations/implications – The model only considered management decision on buffer sizes, batch size and the top bottleneck station alternatives to make improvements. Simulating improvements in labor efficiency, robots uptime, scrap root cause, and maintenance response to downtime where not considered. Practical implications – This paper indicated the importance of discrete simulation modeling in providing alternatives for improving process efficiency under certain financial limitations. Given the similarity of the automotive manufacturing processes among the various companies, the findings for this particular facility remain valid for other facilities. Originality/value – Investment cost and process improvement are currently the two biggest challenges facing operations managers in the manufacturing industry. This study allows managers to gain a broader perspective on discrete simulation ability to simulate complicated systems and present different process improvement alternatives.
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Lu, Na. "Heterogeneous Group Risk Decision Behavior Simulation Based on Particle Swarm Optimization Algorithm." Mobile Information Systems 2022 (July 30, 2022): 1–9. http://dx.doi.org/10.1155/2022/2670241.
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This paper studies the general SoC design AMBA bus and proposes an automatic generation method of software structure test data based on adaptive data optimization algorithm. By simplifying the basic particle expansion equation and eliminating the particle velocity term, an adaptive scheme based on inertia weight is proposed. In the research process, this article fully considers heterogeneous groups. Investment companies are divided into three types of decision-makers: reciprocal, intelligent, and leveraged, and their investment behavior is modeled. Given that factors such as technical level will affect the future of the project, and swarm simulation software is used to simulate and analyze the impact of the profitability of smart community microgrid construction projects on decision-making and to conduct dynamic research on market modeling risks. This article first outlines the construction of the renewable energy macro- and micro-market risk decision-making behavior model and clarifies the logic process of the market to promote the consumption of renewable energy. Then, it analyzes the causes of market risks based on dynamic models, first examines the relationship between key risks and risk factors, forms risks that affect returns (bilateral random risks and market efficiency risks), and then an analysis framework for the impact of renewable energy. This paper applies it to the analysis of data-based algorithms, thereby promoting the development of data-based algorithms.
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Gu, Ruitao, Qingjuan Chen, and Qiaoyun Zhang. "Portfolio Selection with respect to the Probabilistic Preference in Variable Risk Appetites: A Double-Hierarchy Analysis Method." Complexity 2021 (April 17, 2021): 1–14. http://dx.doi.org/10.1155/2021/5512770.
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Traditional portfolio selection models mainly obtain the optimized portfolio ratio by focusing on the prices of financial products. However, investors’ multiple preferences and risk appetites are also significant factors that should be taken into account. In consideration of these two factors simultaneously, we propose a double-hierarchy model in this paper. Specifically, the first hierarchy quantifies investors’ risk appetite based on a historical simulation method and probabilistic preference theory. This hierarchy can be utilized to describe investors’ variable risk appetites and ensure the obtained investment ratios meet investors’ immediate risk requirements. Then, using the cross-efficiency evaluation principle, the optimal investment ratios can be derived by fusing investors’ multiple preferences and risk appetites in the second hierarchy. Lastly, an illustrative example about evaluating the 10 largest capitalized stocks on the Shenzhen Stock Exchange is given to verify the feasibility and effectiveness of our newly proposed model. We make the theoretical contribution to improve the traditional portfolio selection model, especially considering investors’ subjective preferences and risk appetite. Moreover, the proposed model can be practical for assisting investors with their investment strategies in real life.
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Reutov, Viktor Yevgeniyevich, Viktoriya Vladimirovna Reutova, Larisa Аnatolievna Kravchenko, and Irina Аnatolievna Troyan. "BUSINESS SIMULATION AS AN INTERACTIVE METHOD FOR TRAINING ECONOMISTS." Scientific Bulletin: finance, banking, investment., no. 1 (54) (2022): 162–71. http://dx.doi.org/10.37279/2312-5330-2021-1-162-171.
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n the article, the authors identified the essence of the main categories of research: simulation, computer simulation, business simulation. Business simulation is viewed as an interactive method for training economists, which has a system of rules and objectives and is aimed at forming a set of competencies that will help the student in subsequent economic activities. Business simulation has a clearly defined educational goal — the development of practical skills and competencies by the participants. The authors identified the key advantages of using business simulation, including: differentiation and adaptability of model changes; an integrated approach to the study of an object, verifiability of various approaches, the possibility of solving a variety of problems. The authors noted the disadvantages of using business simulation: psychological characteristics of the transition to innovative methods of training students, poor awareness, lack of digital competencies, low motivation of teachers, problems with access to resources and tools. With the use of a systematic analysis of the advantages and disadvantages, the expediency of introducing business simulation into the educational process in higher educational institutions for students of economic training is substantiated. The authors analyzed the experience of using business simulations popular in foreign universities and business schools, including Blue Ocean Strategy Simulation (BOSS), Capsim Capstone Business Simulation, Capsim Foundation, Cesim, Edumundo, Online Simulations Harvard Business Publishing Reality Works Business Education Simulations, Traction. The authors considered Russian projects of business simulations: Business course: Corporation Plus, Nixdorf «Exchange», Nixdorf «Delta», ViAL +. The authors identified economic disciplines, in teaching which business simulation should be used (accounting and audit, economic theory, finance, enterprise economics, management, trade, investment analysis, marketing). This will allow updating education and bringing new business graduates to the market and, as a consequence, increasing the efficiency of the national economy. It was emphasized that further research requires studying the experience of using business simulation games in universities and business schools
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Shukayev, Dulat, Zhanar Lamasheva, Almira Ayapbergenova, and Bimurat Z. "Formalizing the investment selection process of the Development Bank of Kazakhstan." Journal of Finance and Banking Review Vol.2(1) Jan-Mar 2017 2, no. 1 (February 27, 2017): 09–16. http://dx.doi.org/10.35609/jfbr.2017.2.1(2).
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Objective - This article presents a functional diagram for implementing the investment program of the Development Bank of Kazakhstan and builds an outline of the pre-investment evaluation process. Methodology/Technique - A stepwise algorithm is created to conduct a preliminary appraisal of business proposals, and the criteria for assessing the borrower's condition are identified. Key criteria used in the investment performance analysis are discussed. The article develops a computer simulation approach to analysis and decision-making with respect to investment programs, with consideration of analytically non-formalisable stochastic distributions of parameters and processes. The paper also proposes a new method for optimizing the allocation of funds, given various priorities and risks, taking into account the instability and possible ill-conditioning of the optimization problem. Findings - The article formalizes the main stages of Development Bank's pre-investment activities in support of the government's innovative industrial development policy in the country's economy Novelty - Presented models and algorithms of the functional tasks for implementation of investment activities are sufficiently general to be relevant, not only for implementing the government's strategy in this direction, but also for the business interests of any bank or investment entity. Type of Paper: Review Keywords: Investment Selection Process; Development Bank of Kazakhstan; Investment Activities; Business Proposals; Optimizing.
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Wang, Zi Qing, Bin Shen, Zheng Guo Liu, and Jun Qing Liu. "Remote Repair System Based on VIRTOOLS." Advanced Materials Research 791-793 (September 2013): 1028–31. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1028.
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With the increasingly complex new equipment, its maintenance repair training to become a big problem in the process of using the equipment. The traditional training mode by the equipment repair most limit, long development cycle, the characteristics of large investment, based on analysis of virtual repair training system development and function of demand, establish the remote repair system based on VIRTOOLS . The system can create realistic simulation results on the computer, the computer simulation of realistic behavior. The combination of network technology and virtual reality technology organically will provide a technical platform for remote repair service. This paper studies and discusses the architecture of remote repair system based on VIRTOOLS, the key technology and implementation method. And the system structure of remote fault diagnosis system is analyzed.
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Hamid, Agustini. "Accuracy Combination Test of Classical and Modern Technical Analysis: A Case Study in Stock of PT Wijaya Karya Tbk." Binus Business Review 7, no. 1 (May 31, 2016): 71. http://dx.doi.org/10.21512/bbr.v7i1.1465.
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The research aimed to measure the accuracy and combination of Classic and Modern Technical Analysis. PT Wijaya Karya Tbk (WIKA)’s stock in two periods is the sample of research. Technical analysis was used to predict stock prices by observing changes in historical share price. Practically, technical analysis is divided into Classic Technical and Modern. Research was conducted by library study and using a computer software. Microsft Excel was used for the simulation and Chart Nexus for analyzing Modern Technical Analysis. The research period started in January 1, 2013 until December 31, 2013 and January 1, 2014 until December 31, 2014. The Classic Technical Analysis used Support, Resistance, Trendline, and Flag Patern. Meanwhile for Modern Technical Analysis used Moving Average, Stochastic, Moving Average Convergence Divergence (MACD) indicator. The Classical Technical Analysis gave less result than Modern Technical Analysis. The classical give 14 investment decisions in two periods. The average return of Classical Technical is 15,50%. Meanwhile the Modern Technical Analysis gave 18 investment decisions in two periods. The average return of Modern Technical is 18,14%. Combining Classic Technical Analysis and Modern Technical Analysis gave 20 investment decisions with the average rate of return 20,41%.
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Jin, H. P., Jia Rong Li, and Shi Zhong Liu. "Simulation of the Solidification Parameters of Single Crystal Casting." Materials Science Forum 638-642 (January 2010): 2251–56. http://dx.doi.org/10.4028/www.scientific.net/msf.638-642.2251.
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The effects of thermal physical parameters and boundary conditions on investment solidification parameters were obtained using a computer simulation system. Directional solidification parameters of single crystal superalloy include the temperature distribution, the position and the shape of the solid/liquid interface in the mushy zone of the solidifying blade casting. Commercial finite-element analysis software, ProCAST, was used to simulate the solidification processes of the castings of single crystal DD6. The simulation results indicate that the predictions of the temperature show little sensitivity to the thermal physical parameters and boundary conditions. Further, it has also been shown that the location and the shape of solid/liquid interface is related to the boundary conditions of simulation. Increasing the value of interface heat transfer coefficient decreases the width of mushy zone.
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Gottlieb, Paul D., Robin G. Brumfield, Raul I. Cabrera, Daniel Farnsworth, and Lucas Marxen. "An Online Tool for Estimating Return-on-investment for Water Recycling at Nurseries." HortTechnology 32, no. 1 (January 2022): 47–56. http://dx.doi.org/10.21273/horttech04925-21.
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Water availability, quality, and management, particularly under climate change constraints and fierce competition for water resources, are challenging the sustainability of intensively irrigated nursery crops. We created an online tool to estimate costs and benefits of a water recycling investment at a commercial nursery, given data on the operation input by the user. The online tool returns a “regulatory risk score” based on the user’s drought and pollution risk. Then, using a partial budget approach, it returns net present value of the investment, upfront capital cost, and expected change in annual cash flow. The present article seeks to cross-validate this computer model with results reported in the case study literature. We aggregated data on 38 nurseries and greenhouses profiled in five published studies into a meta study dataset. These data validated the computer tool’s assumptions about the relationship of operation size to total capital cost. Separate simulations on the profitability effects of varying public water rates and price premia due to green marketing corroborated the findings of earlier studies. A major finding of the simulation analysis not previously emphasized in the literature is that capital cost and profit vary significantly with the precise method that is used to size the recapture pond. A “minimalist” approach to this decision is likely to be the most cost-effective, but growers should also keep stormwater runoff and other issues of environmental best practices in mind.
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Liu, Wei, Yang Liu, Jun Gu, Jing Zhao, and Rong Zhang. "Tripartite Evolutionary Game Analysis of Financial Support for Science-Tech Enterprises’ Innovation with Government Participation." Computational Intelligence and Neuroscience 2022 (April 30, 2022): 1–21. http://dx.doi.org/10.1155/2022/5207003.
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In this study, we use a tripartite evolutionary game model to analyze the financial support for science-tech enterprises’ innovation with government participation. Based on the game model, the study uses replication dynamics to analyze the stability of evolutionary trajectory in the eight scenarios of enterprises, the government, and the financial institutes. Then, we discuss the effect of the reputation multiplier, the efficiency of firms’ innovation output, and the positive socio-economic externalities multiplier by simulation as the important innovative points in this study. The study draws the following conclusions: (1) enterprises will choose high R&D intensity instead of low R&D intensity if the output of former exceeds that of the latter, (2) enterprises’ R&D output is closely related to the strategy choices of the government and financial institutes, and (3) enterprises can attract government subsidy by boosting economic and social externalities. The government subsidies to enterprises with high R&D intensity will improve the innovation output by the innovation investment and reputation multiplier. So, the government can implement subsidy policy to boost high-intensive R&D activity. Financial institutes’ strategy choice between equity investment and debt investment is influenced by investment yield difference and can influence enterprises’ R&D intensity choices.
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Flegkas, Stylianos, Felix Birkelbach, Franz Winter, Hans Groenewold, and Andreas Werner. "Profitability Analysis and Capital Cost Estimation of a Thermochemical Energy Storage System Utilizing Fluidized Bed Reactors and the Reaction System MgO/Mg(OH)2." Energies 12, no. 24 (December 16, 2019): 4788. http://dx.doi.org/10.3390/en12244788.
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The storage of industrial waste heat through thermochemical energy storage (TCES) shows high potential to reduce the dependency on fossil fuels. In this paper the capital cost investment of a TCES system utilizing fluidized bed reactors and the reaction system MgO/Mg(OH) 2 is estimated and a profitability analysis is performed. The study estimate is based on a simulation study that considers the mass and energy balance of the proposed preliminary heat storage and release processes utilizing fluidized bed reactors. Furthermore, transport, operation and maintenance as well as utility costs were estimated in order to evaluate the profitability of the system. It is concluded that for the selected boundary conditions, the specific investment costs per kW stored heat are approximately 900 €/kW and that the systems should not be installed at sites where less than around 5 MW of waste heat are available. Finally, a sensitivity analysis was conducted, to identify the key process and economic parameters critical for a positive net present value.
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Burlaga, Bartłomiej, Arkadiusz Kroma, Przemysław Poszwa, Robert Kłosowiak, Paweł Popielarski, and Tomasz Stręk. "Heat Transfer Analysis of 3D Printed Wax Injection Mold Used in Investment Casting." Materials 15, no. 19 (September 21, 2022): 6545. http://dx.doi.org/10.3390/ma15196545.
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Investment casting is one of the precise casting methods where disposable wax patterns made in wax injection molds are used to make a casting mold. The production capacity of precision foundry is determined by the time taken for producing wax patterns, which depends on the time taken for wax solidification. Wax injection molds are usually made of aluminum or copper alloys with the use of expensive and time-consuming computer numerical control (CNC) processing, which makes low-volume production unprofitable. To reduce these costs, the authors present a heat transfer analysis of a 3D printed wax injection mold. Due to the low thermal conductivity of the photopolymer resin, the influence of different cooling channels’ shapes was investigated to improve the time of the manufacturing process. Transient thermal analysis was performed using COMSOL software based on the finite element method (FEM) and included a simulation of wax injection mold cooling with cold air (−23 °C), water, and without cooling. The analysis showed that use of cooling channels in the case of photopolymer material significantly reduces the solidification time of the sample (about 10 s shorter), and that under certain conditions, it is possible to obtain better cooling than obtained with the aluminum reference wax injection mold (after approximately 25–30 s). This approach allows to reduce the production costs of low-volume castings.
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Cygan, R., D. Szeliga, P. Rokicki, J. Sieniawski, and J. S. Suchy. "The Control of Solidification Kinetics of the Vacuum-cast Thin-wall Nickel-based Superalloys by Changing the Geometrical Characteristics of the Ceramic Mold." Archives of Foundry Engineering 13, no. 4 (December 1, 2013): 21–28. http://dx.doi.org/10.2478/afe-2013-0076.
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Abstract This paper provides an analysis of experimental research and results of investment casting process. Temperature field in a ceramic mold is one of the problems during numerical simulation. Reducing the costs of production in precision casting involves the reduction of scraps, which is one of the fundamental problems of the foundry industry. Reducing these costs is associated with optimization of precision casting technology of aircraft engines critical parts, including control of the solidification front in thin-walled castings of nickel super alloys cast in a vacuum. It is achieved by changing the geometrical characteristics of the ceramic mold. The results of the tests were used to optimize the industrial production of aircraft components in Precision Foundry of WSK Rzeszów. Temperature distribution gained in the conducted tests allowed verification and optimization of computer simulations.
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De Cesare, Luigi, and Mario Sportelli. "A non-linear approach to Kalecki’s investment cycle." Mathematics and Computers in Simulation 193 (March 2022): 57–70. http://dx.doi.org/10.1016/j.matcom.2021.10.001.
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Manfren, Massimiliano, and Benedetto Nastasi. "Parametric Performance Analysis and Energy Model Calibration Workflow Integration—A Scalable Approach for Buildings." Energies 13, no. 3 (February 1, 2020): 621. http://dx.doi.org/10.3390/en13030621.
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High efficiency paradigms and rigorous normative standards for new and existing buildings are fundamental components of sustainability and energy transitions strategies today. However, optimistic assumptions and simplifications are often considered in the design phase and, even when detailed simulation tools are used, the validation of simulation results remains an issue. Further, empirical evidences indicate that the gap between predicted and measured performance can be quite large owing to different types of errors made in the building life cycle phases. Consequently, the discrepancy between a priori performance assessment and a posteriori measured performance can hinder the development and diffusion of energy efficiency practices, especially considering the investment risk. The approach proposed in the research is rooted on the integration of parametric simulation techniques, adopted in the design phase, and inverse modelling techniques applied in Measurement and Verification (M&V) practice, i.e., model calibration, in the operation phase. The research focuses on the analysis of these technical aspects for a Passive House case study, showing an efficient and transparent way to link design and operation performance analysis, reducing effort in modelling and monitoring. The approach can be used to detect and highlight the impact of critical assumptions in the design phase as well as to guarantee the robustness of energy performance management in the operational phase, providing parametric performance boundaries to ease monitoring process and identification of insights in a simple, robust and scalable way.
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Buła, Dawid, Dariusz Grabowski, Michał Lewandowski, Marcin Maciążek, and Anna Piwowar. "Software Solution for Modeling, Sizing, and Allocation of Active Power Filters in Distribution Networks." Energies 14, no. 1 (December 29, 2020): 133. http://dx.doi.org/10.3390/en14010133.
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The paper is related to the problem of modeling and optimizing power systems supplying, among others, nonlinear loads. A software solution that allows the modeling and simulation of power systems in the frequency domain as well as the sizing and allocation of active power filters has been developed and presented. The basic assumptions for the software development followed by the models of power system components and the optimization assumptions have been described in the paper. On the basis of an example of a low-voltage network, an analysis of the selection of the number and allocation of active power filters was carried out in terms of minimizing losses and investment costs under the assumed conditions for voltage total harmonic distortion (THD) coefficients in the network nodes. The presented examples show that the appropriate software allows for an in-depth analysis of possible solutions and, furthermore, the selection of the optimal one for a specific case, depending on the adopted limitations, expected effects, and investment costs. In addition, a very high computational efficiency of the adopted approach to modeling and simulation has been demonstrated, despite the use of (i) element models for which parameters depend on the operating point (named iterative elements), (ii) active filter models taking into account real harmonics reduction efficiency and power losses, and (iii) a brute force algorithm for optimization.
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Durán, Francisco Jose, Fernando Dorado, and Luz Sanchez-Silva. "Exergetic and Economic Improvement for a Steam Methane-Reforming Industrial Plant: Simulation Tool." Energies 13, no. 15 (July 24, 2020): 3807. http://dx.doi.org/10.3390/en13153807.
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Steam methane reforming (SMR) for hydrogen production was studied by simulating the reformer and pre-reformer sections. This simulation was validated by using available data taken from a real industrial plant, which enabled precise correlations with the real industrial process to be found. Moreover, the influence of the molar ratio between the raw materials (steam-to-carbon molar ratio, S/C) and the reformer outlet temperature (Tcc) was studied. The energy requirements for the reforming reaction increased with the S/C ratio. The energy needed for developing the reforming reaction also increased with Tcc, but the hydrogen yield when operating with a high S/C ratio and Tcc increased. In addition, an exergetic analysis was carried out to identify exergy losses in the SMR process, and most were destroyed in the chemical reactors. Increasing the combustion air flow was proposed for finding an optimum value for exergetic efficiency in the process, thereby reducing fuel consumption. Finally, there was a study into the economic viability of this investment, with a reduction of 22% in utility costs with the optimum exergetic value.
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Xue, Qianyi, Yuewei Ling, and Bingwei Tian. "Portfolio Optimization Model for Gold and Bitcoin Based on Weighted Unidirectional Dual-Layer LSTM Model and SMA-Slope Strategy." Computational Intelligence and Neuroscience 2022 (June 8, 2022): 1–18. http://dx.doi.org/10.1155/2022/1869897.
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Portfolio optimization is one of the most complex problems in the financial field, and technical analysis is a popular tool to find an optimal solution that maximizes the yields. This paper establishes a portfolio optimization model consisting of a weighted unidirectional dual-layer LSTM model and an SMA-slope strategy. The weighted unidirectional dual-layer LSTM model is developed to predict the daily prices of gold/Bitcoin, which addresses the traditional problem of prediction lag. Based on the predicted prices and comparison of two representative investment strategies, simple moving average (SMA) and Bollinger bands (BB), this paper adopts a new investment strategy, SMA-slope strategy, which introduces the concept of k-slope to measure the daily ups and downs of gold/Bitcoin. As two typical financial products, gold and Bitcoin are opposite in terms of their characteristics, which may represent many existing financial products in investors’ portfolios. With a principle of $1000, this paper conducts a five-year simulation of gold and Bitcoin trading from 11 September 2016 to 10 September 2021. To compensate for the SMA and BB that may miss buying and selling points, 4 different parameters’ values in the k-slope are obtained through particle swarm optimization simulation. Also, the simulation results imply that the proposed portfolio optimization model contributes to helping investors make investment decisions with high profitability.
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Chen, Yukai, Sara Vinco, Donkyu Baek, Stefano Quer, Enrico Macii, and Massimo Poncino. "Cost-Aware Design and Simulation of Electrical Energy Systems." Energies 13, no. 11 (June 8, 2020): 2949. http://dx.doi.org/10.3390/en13112949.
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One fundamental dimension in the design of an electrical energy system (EES) is the economic analysis of the possible design alternatives, in order to ensure not just the maximization of the energy output but also the return on the investment and the possible profits. Since the energy output and the economic figures of merit are intertwined, for an accurate analysis it is necessary to analyze these two aspects of the problem concurrently, in order to define effective energy management policies. This paper achieves that objective by tracking and measuring the energy efficiency and the cost effectiveness in a single modular framework. The two aspects are modeled separately, through the definition of dedicated simulation layers governed by dedicated virtual buses that elaborate and manage the information and energy flows. Both layers are simulated concurrently within the same simulation infrastructure based on SystemC-AMS, so as to recreate at runtime the mutual influence of the two aspects, while allowing the use of different discrete time scales for the two layers. Thanks to the tight coupling provided by the single simulation engine, our method enables a quick estimation of various cost metrics (net costs, annualized costs, and profits) of any configuration of EES under design, via an informed exploration of the alternatives. To prove the effectiveness of this approach, we apply the proposed strategy to two EES case studies, we explored various management strategies and the presence of different types and numbers of power sources and energy storage devices in the EES. The analysis proved to allow the identification of the optimal profitable solutions, thereby improving the standard design and simulation flow of EES.
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Barman, Abhijit, Rubi Das, and Pijus Kanti De. "Optimal pricing, replenishment scheduling, and preservation technology investment policy for multi-item deteriorating inventory model under shortages." International Journal of Modeling, Simulation, and Scientific Computing 12, no. 05 (April 23, 2021): 2150039. http://dx.doi.org/10.1142/s1793962321500392.
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In a wholesale shop, the retailer is required to keep an inventory of various ranges of a product due to uncertainty in consumer preferences and behavior. Different Economic Order Quantity (EOQ) models for each variety of a product are needed for optimum level of inventory. EOQ model decides how much stock a shopkeeper has to store, according to demand and deterioration of different items to optimize the inventory policy of multiple products. Items like fashion, food, vegetables, pharmaceuticals, etc., deteriorate in the retailer’s warehouse during storage. An investment is required in preservation technology to significantly reduce the deterioration rate, reduce economic losses, and increase business competitiveness. Here, a multi-item deteriorating EOQ model with a fixed cycle duration has been developed incorporating the preservation technology. The demands for the items are a quadratic function of the selling price, and shortages are allowed. The main objective is to determine the optimal selling price, investment under preservation, the time length up to zero inventory, order quantity of the proposed inventory model such that the overall profit will be maximized. First, we prove that the optimal selling price and investment in preservation exist and are unique. Next, the total profit per unit time is a concave function of selling price and preservation technology investment. An algorithm is designed to obtain the optimum joint policy. A numerical example has been given to illustrate the model, and sensitivity analysis is conducted, which gives some managerial insights.
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Stoilov, Todor, Krasimira Stoilova, and Miroslav Vladimirov. "The Probabilistic Risk Measure VaR as Constraint in Portfolio Optimization Problem." Cybernetics and Information Technologies 21, no. 1 (March 1, 2021): 19–31. http://dx.doi.org/10.2478/cait-2021-0002.
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Abstract The paper realizes inclusion of probabilistic measure for risk, VaR (Value at Risk), into a portfolio optimization problem. The formal analysis of the portfolio problem illustrates the evolution of the portfolio theory in sequentially inclusion of different market characteristics into the problem. They make modifications and complications of the portfolio problem by adding various constraints to consider requirements for taxes, boundaries for assets, cardinality constraints, and allocation of the investment resources. All these characteristics and parameters of the investment participate in the portfolio problem by analytical algebraic relations. The VaR definition of the portfolio risk is formalized in a probabilistic manner. The paper applies approximation of such probabilistic constraint in algebraic form. Geometrical interpretation is given for explaining the influence of the VaR constraint to the portfolio solution. Numerical simulation with data of the Bulgarian Stock Exchange illustrates the influence of the VaR constraint into the portfolio optimization problem.
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Fuchs, Clemens, Joachim Kasten, and Maxi Vent. "Current State and Future Prospective of Repowering Wind Turbines: An Economic Analysis." Energies 13, no. 12 (June 12, 2020): 3048. http://dx.doi.org/10.3390/en13123048.
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For over two decades, the construction of wind turbines in Germany has been supported by guaranteed feed-in tariffs determined by the Renewable Energy Sources Act (EEG), the primary goal of which is climate protection, in addition to reducing the country’s dependence on the import of (finitely available) fossil fuels. After China and the United States, Germany ranks third worldwide in the production of wind energy. The number of onshore wind turbines in Germany has risen to approximately 30,000 plants, of which approximately 10,000 wind turbines will fall out of the guaranteed EEG funding window in the next one to two years. There are basically two alternatives for these wind turbines: either continuing operations, with the sale of electricity at relatively low and fluctuating electricity stock prices, or repowering, which opens access to the fixed feed-in tariffs for another 20 years. However, repowering has the disadvantages that an approval process must be carried out and the investor must participate in a tender. There is no guarantee for the granting of a building permit; economically feasible operations also depend on the fact that one can win a contract without the submitted price being set too low. This area of tension is illustrated by a wind farm in Mecklenburg-Western Pomerania and analysed economically. The investment in new, more efficient, and larger wind turbines currently promises a high return. The profitability of the investment in wind turbines is determined using the net present value (NPV) method. In addition, a risk analysis is carried out using stochastic simulation. As a result, the feed-in tariff contributes to over 95% of the variance in the net present value (NPV).
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D., SOBCHUK,, and DOBROVOLSKA L. "Investigation of parameters of electrical networks by the method of simulation modeling in CAD." Journal of Electrical and power engineering 26, no. 4 (May 24, 2022): 63–68. http://dx.doi.org/10.31474/2074-2630-2022-1-63-68.
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The aim of the work is to increase the efficiency of design processes, provide computer support in operational decision-making in situations requiring rapid collection and synthesis of large amounts of data of different nature, conducting cumbersome computational estimates, including simulation computer modeling. The operation of the network is influenced by both determined, assumed factors and random factors due to changing weather conditions, failures of network equipment, various qualifications of specialists. A well-developed scientific arsenal of mathematical statistics can be used to study regularities, build mathematical models and make forecasts for different investment options. The method of processing experimental data in Excel spreadsheet for periods of trouble-free operation and repair of electrical networks, the method of transition from interval estimates of performance to smooth functions of the electrical network required for computer simulation of labor costs in a continuous time. The concrete example is considered and parameters of work of a city electric network are calculated. Analysis of the results of the calculations showed that the series of obtained probabilities are close to geometric progressions. The method of least squares for each variant of calculations selected such a geometric progression that the differences between the empirical and theoretical curves were minimal. Generalizations of results of calculations are made and requirements to the expert system automating collection of regional data and carrying out computer support of acceptance of administrative decisions are formulated.
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Prina, Matteo Giacomo, Giampaolo Manzolini, David Moser, Roberto Vaccaro, and Wolfram Sparber. "Multi-Objective Optimization Model EPLANopt for Energy Transition Analysis and Comparison with Climate-Change Scenarios." Energies 13, no. 12 (June 23, 2020): 3255. http://dx.doi.org/10.3390/en13123255.
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The modeling of energy systems with high penetration of renewables is becoming more relevant due to environmental and security issues. Researchers need to support policy makers in the development of energy policies through results from simulating tools able to guide them. The EPLANopt model couples a multi-objective evolutionary algorithm to EnergyPLAN simulation software to study the future best energy mix. In this study, EPLANopt is applied at country level to the Italian case study to assess the best configurations of the energy system in 2030. A scenario, the result of the optimization, is selected and compared to the Italian integrated energy and climate action plan scenario. It allows a further reduction of CO2 emissions equal to 10% at the same annual costs of the Italian integrated energy and climate action plan scenario. Both these results are then compared to climate change scenarios through the carbon budget indicator. This comparison shows the difficulties to meet the Paris Agreement target of limiting the temperature increase to 1.5 °C. The results also show that this target can only be met through an increase in the total annual costs in the order of 25% with respect to the integrated energy and climate action plan scenario. However, the study also shows how the shift in expenditure from fossil fuels, external expenses, to investment on the national territory represents an opportunity to enhance the national economy.