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Статті в журналах з теми "Trade-off optimization"

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Audet, Charles, J. E. Dennis, and Sébastien Le Digabel. "Trade-off studies in blackbox optimization." Optimization Methods and Software 27, no. 4-5 (October 2012): 613–24. http://dx.doi.org/10.1080/10556788.2011.571687.

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Nakayama, Hirotaka. "Trade-off analysis using parametric optimization techniques." European Journal of Operational Research 60, no. 1 (July 1992): 87–98. http://dx.doi.org/10.1016/0377-2217(92)90336-8.

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Phillips, Christopher W. G., Dominic A. Hudson, Stephen R. Turnock, and Alexander I. J. Forrester. "Thrust-versus-endurance trade-off optimization in swimming." Engineering Optimization 52, no. 6 (July 17, 2019): 1068–81. http://dx.doi.org/10.1080/0305215x.2019.1636980.

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Giannakis, Mihalis, and Marwa Bouka. "A Trade-off Optimization Model for Container Fulfilment." Supply Chain Forum: An International Journal 16, no. 1 (January 2015): 46–63. http://dx.doi.org/10.1080/16258312.2015.11517366.

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Lee, G. M., and H. Nakayama. "Generalized trade-off directions in multiobjective optimization problems." Applied Mathematics Letters 10, no. 1 (January 1997): 119–22. http://dx.doi.org/10.1016/s0893-9659(96)00122-x.

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Voronin, Albert N. "Trade-Off and Consensus in Vector-Valued Optimization Theory." Journal of Automation and Information Sciences 33, no. 9 (2001): 10. http://dx.doi.org/10.1615/jautomatinfscien.v33.i9.20.

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Alvarez-Hamelin, J. I., and N. Schabanel. "An internet graph model based on trade-off optimization." European Physical Journal B - Condensed Matter 38, no. 2 (March 1, 2004): 231–37. http://dx.doi.org/10.1140/epjb/e2004-00116-y.

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Kuk, Hun, Tetsuzo Tanino, and Masahiro Tanaka. "Trade-off analysis for vector optimization problems via scalarization." Journal of Information and Optimization Sciences 18, no. 1 (January 1997): 75–87. http://dx.doi.org/10.1080/02522667.1997.10699313.

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Lupo, Toni. "Non-dominated “trade-off” solutions in television scheduling optimization." International Transactions in Operational Research 22, no. 3 (December 4, 2014): 563–84. http://dx.doi.org/10.1111/itor.12137.

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Miettinen, Kaisa, and Marko M. Mäkelä. "On generalized trade-off directions in nonconvex multiobjective optimization." Mathematical Programming 92, no. 1 (March 1, 2002): 141–51. http://dx.doi.org/10.1007/s101070100282.

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Дисертації з теми "Trade-off optimization"

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Hawkins, Alicia. "DECISION-MAKER TRADE-OFFS IN MULTIPLE RESPONSE SURFACE OPTIMIZATION." Doctoral diss., University of Central Florida, 2007. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2787.

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The focus of this dissertation is on improving decision-maker trade-offs and the development of a new constrained methodology for multiple response surface optimization. There are three key components of the research: development of the necessary conditions and assumptions associated with constrained multiple response surface optimization methodologies; development of a new constrained multiple response surface methodology; and demonstration of the new method. The necessary conditions for and assumptions associated with constrained multiple response surface optimization methods were identified and found to be less restrictive than requirements previously described in the literature. The conditions and assumptions required for a constrained method to find the most preferred non-dominated solution are to generate non-dominated solutions and to generate solutions consistent with decision-maker preferences among the response objectives. Additionally, if a Lagrangian constrained method is used, the preservation of convexity is required in order to be able to generate all non-dominated solutions. The conditions required for constrained methods are significantly fewer than those required for combined methods. Most of the existing constrained methodologies do not incorporate any provision for a decision-maker to explicitly determine the relative importance of the multiple objectives. Research into the larger area of multi-criteria decision-making identified the interactive surrogate worth trade-off algorithm as a potential methodology that would provide that capability in multiple response surface optimization problems. The ISWT algorithm uses an ε-constraint formulation to guarantee a non-dominated solution, and then interacts with the decision-maker after each iteration to determine the preference of the decision-maker in trading-off the value of the primary response for an increase in value of a secondary response. The current research modified the ISWT algorithm to develop a new constrained multiple response surface methodology that explicitly accounts for decision-maker preferences. The new Modified ISWT (MISWT) method maintains the essence of the original method while taking advantage of the specific properties of multiple response surface problems to simplify the application of the method. The MISWT is an accessible computer-based implementation of the ISWT. Five test problems from the multiple response surface optimization literature were used to demonstrate the new methodology. It was shown that this methodology can handle a variety of types and numbers of responses and independent variables. Furthermore, it was demonstrated that the methodology can be successful using a priori information from the decision-maker about bounds or targets or can use the extreme values obtained from the region of operability. In all cases, the methodology explicitly considered decision-maker preferences and provided non-dominated solutions. The contribution of this method is the removal of implicit assumptions and includes the decision-maker in explicit trade-offs among multiple objectives or responses.
Ph.D.
Department of Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering PhD
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Pang, Xi. "Trade-off analysis of forest ecosystem services – A modelling approach." Doctoral thesis, KTH, Hållbarhet, utvärdering och styrning, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216432.

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Forest is a resource that is increasingly utilized for multiple purposes. The balance between energy demands and the long-term capacity of ecosystems to support biodiversity and other ecosystem services is crucial. The aim of this project was to increase the knowledge on and to develop methods and tools for trade-offs and synergies analysis among forest ecosystem services based on different forest management policies. Paper I provides an overview of existing models for integrated energy-environment assessment. A literature review was conducted on assessment models and their ability to integrate energy with environmental aspects. Missing environmental aspects concern land use, landscapes and biodiversity. In Paper II a modelling framework was set up to link a landscape simulator with a habitat network model for integrated assessment of bioenergy feedstock and biodiversity related impacts in Kronoberg County. In Paper III we continued with the same management scenarios, while the analysis was expanded to five ecosystem services by developing the Landscape simulation and Ecological Assessment (LEcA) tool: industrial wood, bioenergy, forest carbon stock, recreation areas and habitat networks. In Paper IV we present two heuristic methods for spatial optimization – simulated annealing (SA) and genetic algorithm (GA) – to find optimal solutions for allocating harvest activities, in order to minimize the impacts on habitat networks. In Paper V, as response to the findings in Paper I, we linked the energy model MESSAGE with our LEcA tool for forest bioenergy demand assessment while applying environmental and transport restrictions, in a study of Lithuania. We found trade-offs between industrial wood production and bioenergy on one side, and recreation values, biodiversity, and to some extent carbon storage on the other side. The LEcA tool integrated forest simulation and management with assessment of ecosystem services, which is promising for integrated sustainability assessment of forest management policies.

QC 20171023

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Bettemir, Onder Halis. "Optimization Of Time-cost-resource Trade-off Problems In Project Scheduling Using Meta-heuristic Algorithms." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611971/index.pdf.

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In this thesis, meta-heuristic algorithms are developed to obtain optimum or near optimum solutions for the time-cost-resource trade-off and resource leveling problems in project scheduling. Time cost trade-off, resource leveling, single-mode resource constrained project scheduling, multi-mode resource constrained project scheduling and resource constrained time cost trade-off problems are analyzed. Genetic algorithm simulated annealing, quantum simulated annealing, memetic algorithm, variable neighborhood search, particle swarm optimization, ant colony optimization and electromagnetic scatter search meta-heuristic algorithms are implemented for time cost trade-off problems with unlimited resources. In this thesis, three new meta-heuristic algorithms are developed by embedding meta-heuristic algorithms in each other. Hybrid genetic algorithm with simulated annealing presents the best results for time cost trade-off. Resource leveling problem is analyzed by five genetic algorithm based meta-heuristic algorithms. Apart from simple genetic algorithm, four meta-heuristic algorithms obtained same schedules obtained in the literature. In addition to this, in one of the test problems the solution is improved by the four meta-heuristic algorithms. For the resource constrained scheduling problems
genetic algorithm, genetic algorithm with simulated annealing, hybrid genetic algorithm with simulated annealing and particle swarm optimization meta-heuristic algorithms are implemented. The algorithms are tested by using the project sets of Kolisch and Sprecher (1996). Genetic algorithm with simulated annealing and hybrid genetic algorithm simulated annealing algorithm obtained very successful results when compared with the previous state of the art algorithms. 120-activity multi-mode problem set is produced by using the single mode problem set of Kolisch and Sprecher (1996) for the analysis of resource constrained time cost trade-off problem. Genetic algorithm with simulated annealing presented the least total project cost.
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Aminbakhsh, Saman. "Hybrid Particle Swarm Optimization Algorithm For Obtaining Pareto Front Of Discrete Time-cost Trade-off Problem." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615398/index.pdf.

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In pursuance of decreasing costs, both the client and the contractor would strive to speed up the construction project. However, accelerating the project schedule will impose additional cost and might be profitable up to a certain limit. Paramount for construction management, analyses of this trade-off between duration and cost is hailed as the time-cost trade-off (TCT) optimization. Inadequacies of existing commercial software packages for such analyses tied with eminence of discretization, motivated development of different paradigms of particle swarm optimizers (PSO) for three extensions of discrete TCT problems (DTCTPs). A sole-PSO algorithm for concomitant minimization of time and cost is proposed which involves minimal adjustments to shift focus to the completion deadline problem. A hybrid model is also developed to unravel the time-cost curve extension of DCTCPs. Engaging novel principles for evaluation of cost-slopes, and pbest/gbest positions, the hybrid SAM-PSO model combines complementary strengths of overhauled versions of the Siemens Approximation Method (SAM) and the PSO algorithm. Effectiveness and efficiency of the proposed algorithms are validated employing instances derived from the literature. Throughout computational experiments, mixed integer programming technique is implemented to introduce the optimal non-dominated fronts of two specific benchmark problems for the very first time in the literature. Another chief contribution of this thesis can be depicted as potency of SAM-PSO model in locating the entire Pareto fronts of the practiced instances, within acceptable time-frames with reasonable deviations from the optima. Possible further improvements and applications of SAM-PSO model are suggested in the conclusion.
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Bam, Prayag. "Development and Implementation of Network Level Trade-off Analysis tool in Transportation Asset Management." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1512227253641838.

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Sjölund, Björn, and Alex Giang. "An optimization model for the allocation of mobile stroke units : Considering the trade-off between cost and benefit." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-24068.

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Afghari, Amir Pooyan. "Incorporation of road safety into road management systems." Thesis, Concordia University, 2012. https://eprints.qut.edu.au/79838/1/Afghari_MASc_S2012.pdf.

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Road collisions negatively affect the lives of hundreds of Canadians per year. Unfortunately, safety has been typically neglected from management systems. It is common to find that a great deal of effort has been devoted to develop and implement systems capable of achieving and sustaining good levels of condition. It is relatively recent that road safety has become an important objective. Managing a network of roads is not an easy task; it requires long, medium and short term plans to maintain, rehabilitate and upgrade aging assets, reduce and mitigate accident exposure, likelihood and severity. This thesis presents a basis for incorporating road safety into road management systems; two case studies were developed; one limited by available data and another from sufficient information. A long term analysis was used to allocate improvements for condition and safety of roads and bridges, at the network level. It was confirmed that a safety index could be used to obtain a first cut model; meanwhile potential for improvement which is a difference between observed and predicted number of accidents was capable of capturing the degree of safety of individual segments. It was found that the completeness of the system resulted in savings because of the economies obtained from trade-off optimization. It was observed that safety improvements were allocated at the beginning of the analysis in order to reduce the extent of issues, which translated into a systematic reduction of potential for improvement up to a point of near constant levels, which were hypothesized to relate to those unavoidable collisions from human error or vehicle failure.
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Alkhwaildi, Hassan. "TRADE-OFF BETWEEN COST AND CO2 EMISSION IN OPTIMIZATION OF HYBRID RENEWABLE ENERGY SYSTEMS: A CASE STUDY IN SAUDI ARABIA." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/theses/2789.

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Renewable energy sources (RESs) are considered as the most reliable option in the terms of reducing CO2 emission. RESs are known by their low operation and maintenance (O&M) cost and easier installation. In the previous years, their reliability was less due to their uncertainty; however, in the modern days, it is possible to limit RES fluctuations by recently developed technologies such as optimization tools and precise forecasting algorithms. RESs are not always preferred in case studies where the fossil fuels are extremely cheap. In such countries, investors prefer to implement gas turbines or diesel generators regardless of the penalty associated with their negative impacts of such plants on the environmental. Many countries that have low fuel cost are going forward with expanding the conventional power systems with a low growth towards the hybrid renewable power system. This would increase the reliance on sources such as fossil fuels which diminish over time. Moreover, many environmental benefits of the hybrid renewable energy systems (HRES) would not be achieved in which it will be harmful to the environment. Therefore, a trade-off solution is proposed towards solving this problem in which it would make a balance between cost and CO2 emissions. To this end, in this thesis, the objective is to find a reasonable solution (i.e., trade-off) between the cost and the emission. To find such a trade-off, an optimization software called “HOMER Pro” is utilized to identify the optimal design. A compromised solution will be identified with low CO2 emission and low net present cost (NPC). Saudi Arabian Wasit Gas Plant (WGP) owned by Saudi Aramco Company, which is located in a remote area of the country, is chosen as the case study of this thesis. A photovoltaic (PV), wind turbine, reformer, battery, hydrogen tank, and fuel cells are considered to be implemented on the investigated case study.
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Hedgren, Amanda, and Daniel Genberg. "Multi criteria decision making approach for strategic evaluation of environmental trade-off solution in logistics : A case study at Northvolt." Thesis, Luleå tekniska universitet, Institutionen för ekonomi, teknik, konst och samhälle, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-85731.

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The purpose of this thesis is to investigate to what extent the environmental agenda should be taken into consideration during the project phase of logistics at Northvolt. The objective is to build an optimization model for route planning with a trade-off solution for three criteria; cost, emission and time. An abductive research approach is used. The empirical data was collected quantitatively in accordance with cross-industry standard process for data mining. The results obtained from the optimization model were based on an emission calculation framework and weights assigned to the three selected criteria by five decision makers. These results are compared to an as-is analysis of current and of historical transportations as well as to expected future transportations. These results provide insights and emphasize the importance of agility in decision making aiming at the reduction of emissions. The analysis shows that increased costs do not have a clear correlation with reduced emissions or transportation time. It also demonstrates that transporting goods on sea would increase the transportation time but decrease the emissions. The conclusions of the study are that costs can be reduced by 8%, emissions by 6% and transportation time by 14%, compared to their current operations. Short-term recommendations address the need of being agile in the route planning and analyse each shipment individually where the weights of the criteria should be alternated depending on the status of the project. This requires increased communication with the installation team on site and negotiation of contractual rates from additional ports in Sweden. Long-term recommendations emphasise the importance of developing and using emission key performance indicators to set targets in combination with a strategy in order to steer daily operations.
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Jaini, Nor. "An efficient ranking analysis in multi-criteria decision making." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/an-efficient-ranking-analysis-in-multicriteria-decision-making(c5a694d5-fd43-434f-9f9f-b86f7581b97c).html.

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This study is conducted with the aims to develop a new ranking method for multi-criteria decision making problem with conflicting criteria. Such a problem has a set of Pareto solutions, where the act of improving a value of one solution will result in depreciating some of the others. Thus, in this type of problem, there is no unique solution. However, out of many available options, the Decision Maker eventually has to choose only one solution. With this problem as the motivation, the current study develops a compromise ranking algorithm, namely a trade-off ranking method. The trade-off ranking method able to give a trade-off solution with the least compromise compared to other choices as the best solution. The properties of the algorithm are studied in the thesis on several test cases. The proposed method is compared against several multi-criteria decision making methods with ranking based on the distance measure, which are the TOPSIS, relative distance and VIKOR. The sensitivity analysis and uncertainty test are carried out to examine the methods robustness. A critical criteria analysis is also done to test for the most critical criterion in a multi-criteria problem. The decision making method is considered further in a fuzzy environment problem where the fuzzy trade-off ranking is developed and compared against existing fuzzy decision making methods.
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Книги з теми "Trade-off optimization"

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Haimes, Y. Y., W. A. Hall, and H. T. Freedman. Multiobjective Optimization in Water Resources Systems: The Surrogate Worth Trade-Off Method. Elsevier Science & Technology Books, 2011.

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Railsback, Steven F., and Bret C. Harvey. Modeling Populations of Adaptive Individuals. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691195285.001.0001.

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Ecologists now recognize that the dynamics of populations, communities, and ecosystems are strongly affected by adaptive individual behaviors. Yet until now, we have lacked effective and flexible methods for modeling such dynamics. Traditional ecological models become impractical with the inclusion of behavior, and the optimization approaches of behavioral ecology cannot be used when future conditions are unpredictable due to feedbacks from the behavior of other individuals. This book provides a comprehensive introduction to state- and prediction-based theory, or SPT, a powerful new approach to modeling trade-off behaviors in contexts such as individual-based population models where feedbacks and variability make optimization impossible. This book features a wealth of examples that range from highly simplified behavior models to complex population models in which individuals make adaptive trade-off decisions about habitat and activity selection in highly heterogeneous environments. The book explains how SPT builds on key concepts from the state-based dynamic modeling theory of behavioral ecology, and how it combines explicit predictions of future conditions with approximations of a fitness measure to represent how individuals make good—not optimal—decisions that they revise as conditions change. The resulting models are realistic, testable, adaptable, and invaluable for answering fundamental questions in ecology and forecasting ecological outcomes of real-world scenarios.
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Частини книг з теми "Trade-off optimization"

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Golpîra, Hêriş, Heibatolah Sadeghi, and Syed Abdul Rehman Khan. "Time –Cost Trade-off Optimal Approaches." In Application of Mathematics and Optimization in Construction Project Management, 119–40. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81123-5_5.

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Kaveh, A., and V. R. Mahdavi. "Resource Allocation and Time-Cost Trade-Off Using Colliding Bodies Optimization." In Colliding Bodies Optimization, 261–77. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19659-6_10.

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Latotzke, Cecilia, Johnson Loh, and Tobias Gemmeke. "Cascaded Classifier for Pareto-Optimal Accuracy-Cost Trade-Off Using Off-the-Shelf ANNs." In Machine Learning, Optimization, and Data Science, 423–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95470-3_32.

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Miller, George. "MODELING THE CARDIOVASCULAR DISEASE PREVENTION-TREATMENT TRADE-OFF." In Decision Analytics and Optimization in Disease Prevention and Treatment, 323–48. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781118960158.ch15.

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Spiridon, Silvian. "Smart Gain Partitioning for Noise: Linearity Trade-Off Optimization." In Toward 5G Software Defined Radio Receiver Front-Ends, 55–64. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32759-4_5.

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Cowling, Peter, Nic Colledge, Keshav Dahal, and Stephen Remde. "The Trade Off Between Diversity and Quality for Multi-objective Workforce Scheduling." In Evolutionary Computation in Combinatorial Optimization, 13–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11730095_2.

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Jasrasaria, Dipti, and Edward O. Pyzer-Knapp. "Dynamic Control of Explore/Exploit Trade-Off in Bayesian Optimization." In Advances in Intelligent Systems and Computing, 1–15. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01174-1_1.

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Slimani, Mariem, Fernando Silveira, and Philippe Matherat. "Variability-Speed-Consumption Trade-off in Near Threshold Operation." In Integrated Circuit and System Design. Power and Timing Modeling, Optimization, and Simulation, 308–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24154-3_31.

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Sadeghi, Moein, and Ming Lu. "Time-Cost Trade-off Optimization Incorporating Accident Risks in Project Planning." In Lecture Notes in Civil Engineering, 643–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51295-8_45.

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Soviany, Petru, and Radu Tudor Ionescu. "Continuous Trade-off Optimization Between Fast and Accurate Deep Face Detectors." In Neural Information Processing, 473–85. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04179-3_42.

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Тези доповідей конференцій з теми "Trade-off optimization"

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Gur, Ohad, Jonathan Silver, Radovan Dítě, and Raam Sundhar. "PROPELLER OPTIMIZATION - STRIVE TO PERFORMANCE / ACOUSTIC TRADE-OFF." In 14th International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2021. http://dx.doi.org/10.7712/140121.7957.18315.

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Conconi, Paolo, Giovanni Pareschi, Sergio Campana, Oberto Citterio, Marta Civitani, Vincenzo Cotroneo, Laura Proserpio, Gianpiero Tagliaferri, and Giancarlo Parodi. "Design optimization and trade-off study of WFXT optics." In SPIE Optical Engineering + Applications, edited by Stephen L. O'Dell and Giovanni Pareschi. SPIE, 2009. http://dx.doi.org/10.1117/12.827468.

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Wang, Jianyu, Anit Kumar Sahu, Gauri Joshi, and Soummya Kar. "Exploring the Error-Runtime Trade-off in Decentralized Optimization." In 2020 54th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2020. http://dx.doi.org/10.1109/ieeeconf51394.2020.9443529.

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GLEI, Naziha, and Rhaimi Belgacem CHIBANI. "EE-SE Trade-off Optimization for Downlink NOMA Systems." In 2020 17th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2020. http://dx.doi.org/10.1109/ssd49366.2020.9364120.

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Jing, Wang, Zhou Yongsheng, Yang Haoxiong, and Zhang Hao. "A Trade-off Pareto Solution Algorithm for Multi-objective Optimization." In 2012 Fifth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2012. http://dx.doi.org/10.1109/cso.2012.34.

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Oi, Hitoshi. "Power optimization and service level agreement trade-off in SPECjbb2015." In 2016 IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 2016. http://dx.doi.org/10.1109/uemcon.2016.7777880.

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Akyuz, Sureyya, and Buse Cisil Otar. "Ensemble clustering selection by optimization of accuracy-diversity trade off." In 2017 25th Signal Processing and Communications Applications Conference (SIU). IEEE, 2017. http://dx.doi.org/10.1109/siu.2017.7960636.

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Richards, Zach D., and Kimon Valavanis. "Particle Swarm trade-off curve analysis for bi-objective optimization." In 2010 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2010. http://dx.doi.org/10.1109/cec.2010.5586014.

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Yu He, Hongli Zhao, Haitao Yang, Dongjie Zhao, and Yao Yao. "A new Internet evolution model based on trade-off optimization." In IET 3rd International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN 2010). IET, 2010. http://dx.doi.org/10.1049/cp.2010.0619.

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Feth, Denis. "User-centric security: optimization of the security-usability trade-off." In ESEC/FSE'15: Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2786805.2803195.

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Звіти організацій з теми "Trade-off optimization"

1

Steensland, Johan, and Jaideep Ray. A partitioner-centric model for SAMR partitioning trade-off optimization : Part II. Office of Scientific and Technical Information (OSTI), March 2004. http://dx.doi.org/10.2172/918385.

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2

Fernandez, Ruben, Hernando Lugo, and Georfe Dulikravich. Aerodynamic Shape Multi-Objective Optimization for SAE Aero Design Competition Aircraft. Florida International University, October 2021. http://dx.doi.org/10.25148/mmeurs.009778.

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Анотація:
The SAE Regular Class Aero Design Competition requires students to design a radio-controlled aircraft with limits to the aircraft power consumption, take-off distance, and wingspan, while maximizing the amount of payload it can carry. As a result, the aircraft should be designed subject to these simultaneous and contradicting objectives: 1) minimize the aerodynamic drag force, 2) minimize the aerodynamic pitching moment, and 3) maximize the aerodynamic lift force. In this study, we optimized the geometric design variables of a biplane configuration using 3D aerodynamic analysis using the ANSYS Fluent. Coefficients of lift, drag, and pitching moment were determined from the completed 3D CFD simulations. Extracted coefficients were used in modeFRONTIER multi-objective optimization software to find a set of non-dominated (Pareto-optimal or best trade-off) optimized 3D aircraft shapes from which the winner was selected based to the desired plane performance.
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