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Khan, Abdullah, Hashim Hizam, Noor Izzri Abdul-Wahab, and Mohammad Lutfi Othman. "Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm." Energies 13, no. 16 (August 18, 2020): 4265. http://dx.doi.org/10.3390/en13164265.
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In this paper, a multi-objective hybrid firefly and particle swarm optimization (MOHFPSO) was proposed for different multi-objective optimal power flow (MOOPF) problems. Optimal power flow (OPF) was formulated as a non-linear problem with various objectives and constraints. Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. Finally, an optimal compromised solution was selected from the Pareto optimal set by applying an ideal distance minimization method. The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. The achieved results revealed the potential of the proposed algorithm for MOOPF problems.
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Restifo, Richard J. "The Pedicled Robertson Mammaplasty: Minimization of Complications in Obese Patients With Extreme Macromastia." Aesthetic Surgery Journal 40, no. 12 (March 16, 2020): NP666—NP675. http://dx.doi.org/10.1093/asj/sjaa073.
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Abstract Background Breast reduction for extreme macromastia in obese patients is a potentially high-risk endeavor. Free nipple grafting as well as a variety of pedicled techniques have been advocated for large reductions in obese patients, but the number of different approaches suggests that no single method is ideal. This paper suggests the Robertson Mammaplasty, an inferior pedicle technique characterized by a curvilinear skin extension onto the pedicle, as a potentially favorable approach to this clinical situation. Objectives The author sought to determine the safety of the Pedicled Robertson Mammaplasty for extreme macromastia in obese patients. Methods The records of a single surgeon’s practice over a 15-year period were retrospectively reviewed. Inclusion criteria were a Robertson Mammaplasty performed with a >3000-g total resection and a patient weight at least 20% above ideal body weight. Records were reviewed for patient characteristics, operative times, and complications. Results The review yielded 34 bilateral reduction patients that met inclusion criteria. The mean resection weight was 1859.2 g per breast, the mean body mass index was 36.4 kg/m2, and the mean sternal notch-to-nipple distance was 41.4 cm. Mean operative time was 122 minutes. There were no cases of nipple necrosis and no major complications that required reoperation under general anesthesia. A total 26.4% of patients had minor complications that required either local wound care or small office procedures, and 4.4% received small revisions under local anesthesia. Conclusions The Pedicled Robertson Mammaplasty is a fast and safe operation that yields good aesthetic results and a relative minimum of complications in the high-risk group of obese patients with extreme macromastia. Level of Evidence: 4
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Aljohani, Khalid. "Optimizing the Distribution Network of a Bakery Facility: A Reduced Travelled Distance and Food-Waste Minimization Perspective." Sustainability 15, no. 4 (February 16, 2023): 3654. http://dx.doi.org/10.3390/su15043654.
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There are many logistics nuances specific to bakery factories, making the design of their distribution network especially complex. In particular, bakery products typically have a shelf life of under a week. To ensure that products are delivered to end-customers with freshness, speed, quality, health, and safety prioritized, the distribution network, facility location, and ordering system must be optimally designed. This study presents a multi-stage framework for a bakery factory comprised of a selection methodology of an optimum facility location, an effective distribution network for delivery operations, and a practical ordering system used by related supply chain actors. The operations function and distribution network are optimized using a multi-criteria decision-making method comprised of the Analytic Hierarchy Process (AHP) to establish optimization criteria and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) to select the optimal facility location. The optimal distribution network strategy was found using an optimization technique. This framework was applied to a real-life problem for a bakery supply chain in the Western Region, Saudi Arabia. Using a real-life, quantitative dataset and incorporating qualitative feedback from key stakeholders in the supply chain, the developed framework enabled a reduction in overall distribution costs by 14%, decreasing the total travel distance by 16%, and decreasing estimated food waste by 22%. This result was primarily achieved by solving the facility location problem in favor of operating two factories without dedicated storage facilities and implementing the distribution network strategy of direct shipment of products from the bakery to customers.
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GÖÇMEN POLAT, Elifcan. "Distribution Centre Location Selection for Disaster Logistics with Integrated Goal Programming-AHP based TOPSIS Method at the City Level." Afet ve Risk Dergisi 5, no. 1 (June 20, 2022): 282–96. http://dx.doi.org/10.35341/afet.1071343.
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The importance of disaster logistics and its share in the logistics sector are increasing significantly. Most disasters are difficult to predict; therefore, a set of measures seems to be necessary to reduce the risks. Thus, disaster logistics needs to be designed with the pre-disaster and post-disaster measures. These disasters are experienced intensely in Turkey and the importance of these measures becomes more evidential. Therefore, accurate models are required to develop an effective disaster preparedness system. One of the most important decisions to increase the preparedness is to locate the centres for handling material inventory. In this context, this paper analyses the response phase designing the disaster distribution centres in Turkey at the provincial level. AHP (Analytical Hierarchy Process) based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method and goal programming model integration is used to decide alternative locations of distribution centres. TOPSIS method is employed for ranking the locations, which is based on hazard scores, total area, population, and distance to centre. Two conflicting objectives are first proposed in the goal programming formulation, in which maximization of the TOPSIS scores and minimization of the number of distribution centres covering all demands named set covering model are included. Although Gecimli has the highest priority with 0.8 p score in the TOPSIS ranking, Altincevre (0.77) and Buzlupınar (0.75) ensure both the TOPSIS score and coverage of the demand nodes. The results from this paper confirm that the computational results ensure disaster prevention insights especially in regions with limited data.
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Lopez-Perez, Jose J., Uriel H. Hernandez-Belmonte, Juan-Pablo Ramirez-Paredes, Marco A. Contreras-Cruz, and Victor Ayala-Ramirez. "Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection." Mathematical Problems in Engineering 2018 (June 20, 2018): 1–17. http://dx.doi.org/10.1155/2018/2373642.
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In mobile robotics, the exploration task consists of navigating through an unknown environment and building a representation of it. The mobile robot community has developed many approaches to solve this problem. These methods are mainly based on two key ideas. The first one is the selection of promising regions to explore and the second is the minimization of a cost function involving the distance traveled by the robots, the time it takes for them to finish the exploration, and others. An option to solve the exploration problem is the use of multiple robots to reduce the time needed for the task and to add fault tolerance to the system. We propose a new method to explore unknown areas, by using a scene partitioning scheme and assigning weights to the frontiers between explored and unknown areas. Energy consumption is always a concern during the exploration, for this reason our method is a distributed algorithm, which helps to reduce the number of communications between robots. By using this approach, we also effectively reduce the time needed to explore unknown regions and the distance traveled by each robot. We performed comparisons of our approach with state-of-the-art methods, obtaining a visible advantage over other works.
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Shu Xuan, Leong, Tengku Juhana Tengku Hashim, and Muhamad Najib Kamarudin. "Optimal location and sizing of distributed generation to minimize losses using whale optimization algorithm." Indonesian Journal of Electrical Engineering and Computer Science 29, no. 1 (January 1, 2022): 15. http://dx.doi.org/10.11591/ijeecs.v29.i1.pp15-23.
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The conventional power plants often bring in power quality concerns for instance high power losses and poor voltage profile to the network which are caused by the locations of power plants that are placed a distance away from loads. With proper planning and systematic allocation, the introduction of distributed generation (DG) into the network will enhance the performance and condition of the power system. This paper utilizes the optimization approach named whale optimization algorithm (WOA) in the search of the most ideal location and size of DG while ensuring the reduction of power losses and the minimization of the voltage deviation. WOA implementation is done in the IEEE 33-bus radial distribution system (RDS) utilizing MATPOWER and MATLAB software for no DG, one DG and two DGs installation. The outcome obtained from using WOA was compared to other well-known optimization methods and WOA has shown its competency after comparison; the optimal location of WOA with other methods showing almost the same result. The best result presented was the system with two DGs installed due to the losses of the system was recorded to be the least compared to one DG or no DG installation.
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He, Chun, Ke Guo, and Huayue Chen. "An Improved Image Filtering Algorithm for Mixed Noise." Applied Sciences 11, no. 21 (November 4, 2021): 10358. http://dx.doi.org/10.3390/app112110358.
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In recent years, image filtering has been a hot research direction in the field of image processing. Experts and scholars have proposed many methods for noise removal in images, and these methods have achieved quite good denoising results. However, most methods are performed on single noise, such as Gaussian noise, salt and pepper noise, multiplicative noise, and so on. For mixed noise removal, such as salt and pepper noise + Gaussian noise, although some methods are currently available, the denoising effect is not ideal, and there are still many places worthy of improvement and promotion. To solve this problem, this paper proposes a filtering algorithm for mixed noise with salt and pepper + Gaussian noise that combines an improved median filtering algorithm, an improved wavelet threshold denoising algorithm and an improved Non-local Means (NLM) algorithm. The algorithm makes full use of the advantages of the median filter in removing salt and pepper noise and demonstrates the good performance of the wavelet threshold denoising algorithm and NLM algorithm in filtering Gaussian noise. At first, we made improvements to the three algorithms individually, and then combined them according to a certain process to obtain a new method for removing mixed noise. Specifically, we adjusted the size of window of the median filtering algorithm and improved the method of detecting noise points. We improved the threshold function of the wavelet threshold algorithm, analyzed its relevant mathematical characteristics, and finally gave an adaptive threshold. For the NLM algorithm, we improved its Euclidean distance function and the corresponding distance weight function. In order to test the denoising effect of this method, salt and pepper + Gaussian noise with different noise levels were added to the test images, and several state-of-the-art denoising algorithms were selected to compare with our algorithm, including K-Singular Value Decomposition (KSVD), Non-locally Centralized Sparse Representation (NCSR), Structured Overcomplete Sparsifying Transform Model with Block Cosparsity (OCTOBOS), Trilateral Weighted Sparse Coding (TWSC), Block Matching and 3D Filtering (BM3D), and Weighted Nuclear Norm Minimization (WNNM). Experimental results show that our proposed algorithm is about 2–7 dB higher than the above algorithms in Peak Signal-Noise Ratio (PSNR), and also has better performance in Root Mean Square Error (RMSE), Structural Similarity (SSIM), and Feature Similarity (FSIM). In general, our algorithm has better denoising performance, better restoration of image details and edge information, and stronger robustness than the above-mentioned algorithms.
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Jawak, Shridhar D., Sagar F. Wankhede, Alvarinho J. Luis, and Keshava Balakrishna. "Impact of Image-Processing Routines on Mapping Glacier Surface Facies from Svalbard and the Himalayas Using Pixel-Based Methods." Remote Sensing 14, no. 6 (March 15, 2022): 1414. http://dx.doi.org/10.3390/rs14061414.
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Glacier surface facies are valuable indicators of changes experienced by a glacial system. The interplay of accumulation and ablation facies, followed by intermixing with dust and debris, as well as the local climate, all induce observable and mappable changes on the supraglacial terrain. In the absence or lag of continuous field monitoring, remote sensing observations become vital for maintaining a constant supply of measurable data. However, remote satellite observations suffer from atmospheric effects, resolution disparity, and use of a multitude of mapping methods. Efficient image-processing routines are, hence, necessary to prepare and test the derivable data for mapping applications. The existing literature provides an application-centric view for selection of image processing schemes. This can create confusion, as it is not clear which method of atmospheric correction would be ideal for retrieving facies spectral reflectance, nor are the effects of pansharpening examined on facies. Moreover, with a variety of supervised classifiers and target detection methods now available, it is prudent to test the impact of variations in processing schemes on the resultant thematic classifications. In this context, the current study set its experimental goals. Using very-high-resolution (VHR) WorldView-2 data, we aimed to test the effects of three common atmospheric correction methods, viz. Dark Object Subtraction (DOS), Quick Atmospheric Correction (QUAC), and Fast Line-of-Sight Atmospheric Analysis of Hypercubes (FLAASH); and two pansharpening methods, viz. Gram–Schmidt (GS) and Hyperspherical Color Sharpening (HCS), on thematic classification of facies using 12 supervised classifiers. The conventional classifiers included: Mahalanobis Distance (MHD), Maximum Likelihood (MXL), Minimum Distance to Mean (MD), Spectral Angle Mapper (SAM), and Winner Takes All (WTA). The advanced/target detection classifiers consisted of: Adaptive Coherence Estimator (ACE), Constrained Energy Minimization (CEM), Matched Filtering (MF), Mixture-Tuned Matched Filtering (MTMF), Mixture-Tuned Target-Constrained Interference-Minimized Filter (MTTCIMF), Orthogonal Space Projection (OSP), and Target-Constrained Interference-Minimized Filter (TCIMF). This experiment was performed on glaciers at two test sites, Ny-Ålesund, Svalbard, Norway; and Chandra–Bhaga basin, Himalaya, India. The overall performance suggested that the FLAASH correction delivered realistic reflectance spectra, while DOS delivered the least realistic. Spectra derived from HCS sharpened subsets seemed to match the average reflectance trends, whereas GS reduced the overall reflectance. WTA classification of the DOS subsets achieved the highest overall accuracy (0.81). MTTCIMF classification of the FLAASH subsets yielded the lowest overall accuracy of 0.01. However, FLAASH consistently provided better performance (less variable and generally accurate) than DOS and QUAC, making it the more reliable and hence recommended algorithm. While HCS-pansharpened classification achieved a lower error rate (0.71) in comparison to GS pansharpening (0.76), neither significantly improved accuracy nor efficiency. The Ny-Ålesund glacier facies were best classified using MXL (error rate = 0.49) and WTA classifiers (error rate = 0.53), whereas the Himalayan glacier facies were best classified using MD (error rate = 0.61) and WTA (error rate = 0.45). The final comparative analysis of classifiers based on the total error rate across all atmospheric corrections and pansharpening methods yielded the following reliability order: MXL > WTA > MHD > ACE > MD > CEM = MF > SAM > MTMF = TCIMF > OSP > MTTCIMF. The findings of the current study suggested that for VHR visible near-infrared (VNIR) mapping of facies, FLAASH was the best atmospheric correction, while MXL may deliver reliable thematic classification. Moreover, an extensive account of the varying exertions of each processing scheme is discussed, and could be transferable when compared against other VHR VNIR mapping methods.
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H. Mohammed, Abbas, and Khattab S. Abdul-Razzaq. "Optimum Design of Steel Trapezoidal Box-Girders Using Finite Element Method." International Journal of Engineering & Technology 7, no. 4.20 (November 28, 2018): 325. http://dx.doi.org/10.14419/ijet.v7i4.20.26130.
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The target of basic plan is to choose part sizes with the ideal proportioning of the in general auxiliary geometry. Regular steel trapezoidal box-supports have been utilized generally in different designing fields. The target of this examination is to create three-dimensional limited component display for the size improvement of steel trapezoidal box-braces. The limited component programming bundle ANSYS was utilized to decide the ideal cross segment measurement for the steel trapezoidal-box support. Two target capacities were considered in this investigation which are: minimization of the strain vitality and minimization of the volume. The plan factors are the width of the best spine, the width of the base rib, the thickness of the best rib, the thickness of the base rib, the stature of the support and the thickness of the networks. The imperatives considered in this examination are the ordinary and shear worry in steel brace and the dislodging at mid-length of the support. Improvement consequences of steel brace show that the ideal territory of cross segment for the strain vitality minimization is more noteworthy than the ideal for volume minimization by 6 %. The base cross area is the financial structure, hence the volume minimization is more pertinence for steel brace advancement.
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Rozylowicz, Laurentiu, Florian P. Bodescu, Cristiana M. Ciocanea, Athanasios A. Gavrilidis, Steluta Manolache, Marius L. Matache, Iulia V. Miu, Ionut C. Moale, Andreea Nita, and Viorel D. Popescu. "Empirical analysis and modeling of Argos Doppler location errors in Romania." PeerJ 7 (January 31, 2019): e6362. http://dx.doi.org/10.7717/peerj.6362.
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Background Advances in wildlife tracking technology have allowed researchers to understand the spatial ecology of many terrestrial and aquatic animal species. Argos Doppler is a technology that is widely used for wildlife tracking owing to the small size and low weight of the Argos transmitters. This allows them to be fitted to small-bodied species. The longer lifespan of the Argos units in comparison to units outfitted with miniaturized global positioning system (GPS) technology has also recommended their use. In practice, large Argos location errors often occur due to communication conditions such as transmitter settings, local environment, and the behavior of the tracked individual. Methods Considering the geographic specificity of errors and the lack of benchmark studies in Eastern Europe, the research objectives were: (1) to evaluate the accuracy of Argos Doppler technology under various environmental conditions in Romania, (2) to investigate the effectiveness of straightforward destructive filters for improving Argos Doppler data quality, and (3) to provide guidelines for processing Argos Doppler wildlife monitoring data. The errors associated with Argos locations in four geographic locations in Romania were assessed during static, low-speed and high-speed tests. The effectiveness of the Douglas Argos distance angle filter algorithm was then evaluated to ascertain its effect on the minimization of localization errors. Results Argos locations received in the tests had larger associated horizontal errors than those indicated by the operator of the Argos system, including under ideal reception conditions. Positional errors were similar to those obtained in other studies outside of Europe. The errors were anisotropic, with larger longitudinal errors for the vast majority of the data. Errors were mostly related to speed of the Argos transmitter at the time of reception, but other factors such as topographical conditions and orientation of antenna at the time of the transmission also contributed to receiving low-quality data. The Douglas Argos filter successfully excluded the largest errors while retaining a large amount of data when the threshold was set to the local scale (two km). Discussion Filter selection requires knowledge about the movement patterns and behavior of the species of interest, and the parametrization of the selected filter typically requires a trial and error approach. Selecting the proper filter reduces the errors while retaining a large amount of data. However, the post-processed data typically includes large positional errors; thus, we recommend incorporating Argos error metrics (e.g., error ellipse) or use complex modeling approaches when working with filtered data.
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Mamta,, Mamta,, U. Nangia, and N. K. Jain. "Genetic Algorithm based Multiobjective Optimal Power Dispatch based on Ideal Distance Minimization." IOSR Journal of Electrical and Electronics Engineering 9, no. 2 (2014): 39–48. http://dx.doi.org/10.9790/1676-09273948.
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Nangia, U., N. K. Jain, and C. L. Wadhwa. "Multiobjective optimal load flow based on ideal distance minimization in 3D space." International Journal of Electrical Power & Energy Systems 23, no. 8 (November 2001): 847–55. http://dx.doi.org/10.1016/s0142-0615(00)00085-5.
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Asady, B. "Revision of distance minimization method for ranking of fuzzy numbers." Applied Mathematical Modelling 35, no. 3 (March 2011): 1306–13. http://dx.doi.org/10.1016/j.apm.2010.09.007.
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Martyshko, Petr, Igor Ladovskii, Denis Byzov, and Alexander Tsidaev. "Gravity Data Inversion with Method of Local Corrections for Finite Elements Models." Geosciences 8, no. 10 (October 10, 2018): 373. http://dx.doi.org/10.3390/geosciences8100373.
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We present a new method for gravity data inversion for the linear problem (reconstruction of density distribution by given gravity field). This is an iteration algorithm based on the ideas of local minimization (also known as local corrections method). Unlike the gradient methods, it does not require a nonlinear minimization, is easier to implement and has better stability. The algorithm is based on the finite element method. The finite element approach in our study means that the medium (part of a lithosphere) is represented as a set of equal rectangular prisms, each with constant density. We also suggest a time-efficient optimization, which speeds up the inversion process. This optimization is applied on the gravity field calculation stage, which is a part of every inversion iteration. Its idea is to replace multiple calculations of the gravity field for all finite elements in all observation points with a pre-calculated set of uniform fields for all distances between finite element and observation point, which is possible for the current data set. Method is demonstrated on synthetic data and real-world cases. The case study area is located on the Timan-Pechora plate. This region is one of the promising oil- and gas-producing areas in Russia. Note that in this case we create a 3D density model using joint interpretation of seismic and gravity data.
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Rudy, Jarosław, Radosław Idzikowski, Elzbieta Roszkowska, and Konrad Kluwak. "Multiple Mobile Robots Coordination in Shared Workspace for Task Makespan Minimization." Processes 10, no. 10 (October 15, 2022): 2087. http://dx.doi.org/10.3390/pr10102087.
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In this paper we consider a system of multiple mobile robots (MMRS) and the process of their concurrent motion in a shared two-dimensional workspace. The goal is to plan the robot movement along given fixed paths so as to minimize the completion time of all the robots while ensuring that they never collide. Thus, the considered problem combines the problems of robot schedule optimization with collision and deadlock avoidance. The problem formulation is presented and its equivalent reformulation that does not depend explicitly on the geometry of the robot paths is proposed. An event-based solution representation is proposed, allowing for a discrete optimization approach. Two types of possible deadlocks are identified and deadlock avoidance procedures are discussed. We proposed two types of solving methods. First, we implemented two metaheuristics: the local-search-based taboo search as well as the population-based artificial bee colony. Next, we implemented 14 simple constructive algorithms, employing dispatch rules such as first-in first-out, shortest distance remaining first, and longest distance remaining first, among others. A set of problem instances for different numbers of robots is created and provided as a benchmark. The effectiveness of the solving methods is then evaluated by simulation using the generated instances. Both deterministic and lognormal-distributed uncertain robot travel times are considered. The results prove that the taboo search metaheuristic obtained the best results for both deterministic and uncertain cases, with only artificial bee colony and a few constructive algorithms managing to remain competitive. Detailed results as well as ideas to further improve proposed methods are discussed.
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Tubniyom, Chayut, Rongrit Chatthaworn, Amnart Suksri, and Tanakorn Wongwuttanasatian. "Minimization of Losses in Solar Photovoltaic Modules by Reconfiguration under Various Patterns of Partial Shading." Energies 12, no. 1 (December 22, 2018): 24. http://dx.doi.org/10.3390/en12010024.
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Configurations of photovoltaic (PV) modules, such as series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT) configurations, always utilize a number of connecting switches. In a simulation, the ideal switch with no loss is used to optimize the reconfiguration method for a solar PV array. However, in practice, the switches are non-ideal, causing losses and resulting in a decrease in the total output power of the PV array. In this work, MATLAB/Simulink (R2016a) was employed to simulate nine PV modules linked in a 3 × 3 array, and they were reconfigured using series-parallel (SP), bridge-linked (BL), and total cross-tied (TCT) configurations for both ideal and non-ideal switch cases. It was not surprising that non-ideal switches deteriorated the output power compared with ideal cases. Then, the minimization of losses (ML) configuration was proposed by minimizing the number of switches to give the highest output power. A 5% higher power output was set as the criterion to reconfigure the PV modules when partial shading occurred. The results showed that if 50% or more of the area was partially shaded, reconfiguration was unnecessary. On the other hand, when the shaded area was less than 50%, reconfiguration gave a significant increase in power. Finally, the ML method had different configurations for various shading patterns, and provided better results than those of the TCT method.
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Zhang, Huajin, Shunchuan Wu, Xiaoqiang Zhang, Longqiang Han, and Zhongxin Zhang. "Slope stability prediction method based on the margin distance minimization selective ensemble." CATENA 212 (May 2022): 106055. http://dx.doi.org/10.1016/j.catena.2022.106055.
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SALUKVADZE, M. E., R. SH GOGSADZE, and N. I. JIBLADZE. "TO THE FORMALIZATION OF THE ESTIMATES OF THE PHENOMENON STATE." International Journal of Information Technology & Decision Making 06, no. 04 (December 2007): 599–610. http://dx.doi.org/10.1142/s0219622007002708.
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The questions of the formalization of the estimates of the phenomenon state, which can be used in the decision-making multicriterion problems [Vector-Valued Optimization Problems in Control Theory (Academic Press, New York, 1979)] taking into account the metrics of the space of partial criteria are considered. Any phenomenon is described by some system of characteristic parameters, which values are presented by the coordinates of points in the space of states of the given phenomenon. A notion of the "ideal" state determined by optimal values of each characteristic parameter separately and independently of others is used. Estimate of any state is determined by the distance between that state and the "ideal" one. That permits to choose from a multitude of the given states the best one, to which conforms a minimum distance to the "ideal" state. In the general case of the curved space the distances are measured by geodesic lines drawn by using a metric tensor of the given space. The metric tensor components themselves are determined by the solution of the differential equations set up from the condition of minimization of a certain functional.
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Nan, Jiangxia, Ting Wang, and Jingjing An. "Intuitionistic Fuzzy Distance Based TOPSIS Method and Application to MADM." International Journal of Fuzzy System Applications 5, no. 1 (January 2016): 43–56. http://dx.doi.org/10.4018/ijfsa.2016010103.
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In this paper, an intuitionistic fuzzy (IF) distance measure between two triangular intuitionistic fuzzy numbers (TIFNs) is developed. The metric properties of the proposed IF distance measure are also studied. Then, based on this IF distance, an extended TOPSIS is developed to solve multi-attribute decision making (MADM) problems with the ratings of alternatives on attributes of TIFNs. In this methodology, the IF distances between each alternative and the TIFN positive ideal-solution are calculated as well as the TIFN negative ideal-solution. Then the relative closeness degrees obtained of each alternative to the TIFN positive ideal solution are TIFNs. Based on the ranking methods of TIFNs the alternatives are ranked. A numerical example is examined to the validity and practicability of the method proposed in this paper.
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Spasojevic, Momcilo, Milovan Jankovic, and Damir Djakovic. "A new approach to entropy production minimization in diabatic distillation column with trays." Thermal Science 14, no. 2 (2010): 317–28. http://dx.doi.org/10.2298/tsci1002317s.
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Previous approach to direct numerical minimization of entropy production in diabatic distillation column in order to determine heat quantity to be exchanged at trays was based on temperatures on trays as control variables and it was applied only to simple binary columns. Also, previously developed theoretical models for determining optimal exchanged heat profile were determined only at such columns and while they were approximated they produced worse results than numerical minimum of entropy production. In this paper, as control variables for minimization, exchanged heat on the trays is used. It enables application to complex multicomponent diabatic columns. Ishii-Otto global method, based on model linearization and iterative solution by Newton-Raphson technique, is applied for solving column mathematical model. Needed thermodynamical properties for ideal systems are calculated using Lewis-Randall ideal solution model, and for non-ideal slightly polar systems they are calculated using Soave equation of state. Five direct methods are used for numerical optimization. Applied approach is successfully demonstrated at frequently used example of distillation of benzene and toluol mixture by using for these purposes specially written program. Simplex method appeared to be the most convenient optimization method for the considered problem.
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LI, HONGZHI, and YAOQI ZHOU. "FOLD HELICAL PROTEINS BY ENERGY MINIMIZATION IN DIHEDRAL SPACE AND A DFIRE-BASED STATISTICAL ENERGY FUNCTION." Journal of Bioinformatics and Computational Biology 03, no. 05 (October 2005): 1151–70. http://dx.doi.org/10.1142/s0219720005001430.
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Statistical energy functions are discrete (or stepwise) energy functions that lack van der Waals repulsion. As a result, they are often applied directly to a given structure (native or decoy) without further energy minimization being performed to the structure. However, the full benefit (or hidden defect) of an energy function cannot be revealed without energy minimization. This paper tests a recently developed, all-atom statistical energy function by energy minimization with a fixed secondary helical structure in dihedral space. This is accomplished by combining the statistical energy function based on a distance-scaled finite ideal-gas reference (DFIRE) state with a simple repulsive interaction and an improper torsion energy function. The energy function was used to minimize 2000 random initial structures of 41 small and medium-sized helical proteins in a dihedral space with a fixed helical region. Results indicate that near-native structures for most studied proteins can be obtained by minimization alone. The average minimum root-mean-squared distance (rmsd) from the native structure for all 41 proteins is 4.1 Å. The energy function (together with a simple clustering of similar structures) also makes a reasonable selection of near-native structures from minimized structures. The average rmsd value and the average rank for the best structure in the top five is 6.8 Å and 2.4, respectively. The accuracy of the structures sampled and the structure selections can be improved significantly with the removal of flexible terminal regions in rmsd calculations and in minimization and with the increase in the number of minimizations. The minimized structures form an excellent decoy set for testing other energy functions because most structures are well-packed with minimum hard-core overlaps with correct hydrophobic/hydrophilic partitioning. They are available online at .
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Fushimi, Takayasu, Kazumi Saito, and Hiroshi Motoda. "Constructing outlier-free histograms with variable bin-width based on distance minimization." Intelligent Data Analysis 27, no. 1 (January 30, 2023): 5–29. http://dx.doi.org/10.3233/ida-216316.
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We propose a new method of constructing a variable bin width histogram that can accommodate the unbalanced distribution of the samples yet retaining, as a whole, the good aspect of both equal width (EW) and equal-area (EA) histograms that are being used popularly for data visualization and analysis. We formulate this as an optimal change point detection problem in which the bin boundaries are determined by minimizing the sum of the absolute error or the squared error in each bin. The former is based on Distance Minimization (DM) and new, and the latter is based on Variance Minimization (VM) and is considered the state-of-the-art. The constructed histograms can effectively be used to detect and visualize hidden outliers/anomalies by applying the interquartile range method in each bin. The final histograms are obtained by adjusting bin boundaries and heights accordingly after removing the detected outliers/anomalies. We further propose a method to annotate the constructed bins if the data for annotation is given for each sample as a set of nominal variables, using z-score with respect to their distribution within each bin. We applied our method to both real vinyl greenhouse datasets and two different sets of three synthetic datasets, and confirmed that both DM and VM methods work as intended, both can represent the sample distribution with a smaller number of bins than those by EW and EA methods, The use of interquartile range method can detect anomalies as well as outliers, and the terms selected for annotation are interpretable and reasonable. EW and EA methods have contrasting properties. DM and VM methods lie in between, but the former is closer to EA method and the latter to EW method. DM method runs substantially faster than VM method and performs slightly better than VM method in outlier detection and annotation tasks.
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Chang, C., M. J. Chung, and Z. Bien. "Collision-free motion planning for two articulated robot arms using minimum distance functions." Robotica 8, no. 2 (April 1990): 137–44. http://dx.doi.org/10.1017/s0263574700007712.
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SummaryThis paper presents a collision-free motion planning method of two articulated robot arms in a three dimensional common work space. Each link of a robot arm is modeled by a cylinder ended by two hemispheres, and the remaining wrist and hand is modeled by a sphere. To describe the danger of collision between two modeled objects, minimum distance functions, which are defined by the Euclidean norm, are used. These minimum distance functions are used to describe the constraints that guarantee no collision between two robot arms. The collision-free motion planning problem is formulated as a pointwise constrained nonlinear minimization problem, and solved by a conjugate gradient method with barrier functions. To improve the minimization process, a simple grid technique is incorporated. Finally, a simulation study is presented to show the significance of the proposed method.
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Shi, Ya, and Hongbing Ji. "Smooth approximation method for non-smooth empirical risk minimization based distance metric learning." Neurocomputing 127 (March 2014): 135–43. http://dx.doi.org/10.1016/j.neucom.2013.08.030.
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Liu, Peide. "MULTI‐ATTRIBUTE DECISION‐MAKING METHOD RESEARCH BASED ON INTERVAL VAGUE SET AND TOPSIS METHOD." Technological and Economic Development of Economy 15, no. 3 (September 30, 2009): 453–63. http://dx.doi.org/10.3846/1392-8619.2009.15.453-463.
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This paper proposed a method to resolve the multi‐attribute decision‐making problem using TOPSIS method based on attribute weights and attribute values are all interval vague value. Firstly, based on the operation rules of the interval Vague value, the interval Vague attribute value is made by weighted operation, and the ideal and negative ideal solutions are calculated based on the score function. Then the distance of interval Vague value is defined, as well as the distance between each project and the ideal, and negative ideal solutions. The relative adjacent degree is calculated by TOPSIS method, then the order of the projects is confirmed according to the relative adjacent degree. Finally, a case is used to show the process of the method this paper proposed and the validity of this method is proved. Santrauka Straipsnyje siūlomas daugiakriterinės sprendimo priėmimo problemos sprendimas TOPSIS metodu, kai kriterijų reikšmingumai ir reikšmės yra intervaliniai dydžiai. Iš pradžių, naudojantis procedūromis, nustatomos svertinės intervalinių dydžių reikšmės, paskui apskaičiuojami idealiai teigiamas ir idealiai negiamas sprendiniai. Toliau nustatomi intervalų dydžiai, apskaičiuojami atstumai tarp kiekvienos alternatyvos ir idealiai teigiamo ir idealiai neigiamo sprendinių. TOPSIS metodu apskaičiuojami santykiniai atstumai iki minėtų idealių sprendinių ir alternatyvos išrikuojamos į eilę. Galiausiai konkrečiu pavyzdžiu demonstruojamas skaičiavimo procesas ir patvirtinamas siūlomo metodo pagrįstumas.
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Tavana, Madjid, Frank LoPinto, and James W. Smither. "A Hybrid Distance-Based Ideal-Seeking Consensus Ranking Model." Journal of Applied Mathematics and Decision Sciences 2007 (August 19, 2007): 1–18. http://dx.doi.org/10.1155/2007/20489.
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Ordinal consensus ranking problems have received much attention in the management science literature. A problem arises in situations where a group of k decision makers (DMs) is asked to rank order n alternatives. The question is how to combine the DM rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking; however, the similarity of consensus rankings generated by the different algorithms is largely unknown. In this paper, we propose a new hybrid distance-based ideal-seeking consensus ranking model (DCM). The proposed hybrid model combines parts of the two commonly used consensus ranking techniques of Beck and Lin (1983) and Cook and Kress (1985) into an intuitive and computationally simple model. We illustrate our method and then run a Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda and Kendall (Kendall 1962) and the two methods proposed by Beck and Lin (1983) and Cook and Kress (1985). DCM and Beck and Lin's method yielded the most similar consensus rankings, whereas the Cook-Kress method and the Borda-Kendall method yielded the least similar consensus rankings.
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Morosuk, Tatiana, Ruslan Nikulshin, and Larisa Morosuk. "Entropy-cycle method for analysis of refrigeration machine and heat pump cycles." Thermal Science 10, no. 1 (2006): 111–24. http://dx.doi.org/10.2298/tsci0601111m.
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Real and ideal cycles of any complexity can be compared through the definition of the irreversibility's and ways of their minimization in the thermodynamic analysis. The paper considers the use of entropy-cycle method for thermodynamic analysis of refrigerating machines and heat pumps. Using this method preconditions of practical use for analysis, synthesis, and optimization have been created. The methodology of the entropy-cycle method can be use in many areas of the scientific work and educational process.
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U.O., Eric, Michael O.O., Oberhiri-Orumah G., and Chike H. N. "New K-means Clustering Method Using Minkowski’s Distance as its Metric." British Journal of Computer, Networking and Information Technology 4, no. 1 (July 6, 2021): 28–41. http://dx.doi.org/10.52589/bjcnit-xepsjbwx.
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Cluster analysis is an unsupervised learning method that classifies data points, usually multidimensional into groups (called clusters) such that members of one cluster are more similar (in some sense) to each other than those in other clusters. In this paper, we propose a new k-means clustering method that uses Minkowski’s distance as its metric in a normed vector space which is the generalization of both the Euclidean distance and the Manhattan distance. The k-means clustering methods discussed in this paper are Forgy’s method, Lloyd’s method, MacQueen’s method, Hartigan and Wong’s method, Likas’ method and Faber’s method which uses the usual Euclidean distance. It was observed that the new k-means clustering method performed favourably in comparison with the existing methods in terms of minimization of the total intra-cluster variance using simulated data and real-life data sets.
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Li, Jin-qiu, Wei Chen, Zao-li Yang, and Chuan-yun Li. "A time-preference and VIKOR-based dynamic intuitionistic fuzzy decision making method." Filomat 32, no. 5 (2018): 1523–33. http://dx.doi.org/10.2298/fil1805523l.
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According to the decision information of multi-attribute decision-making problem with fuzzy and temporal characteristics, a dynamic intuitionistic fuzzy decision making method based on time preference and VIKOR is proposed. First, we determined the attribute weights under different time sequence based on intuitionistic fuzzy entropy minimization; secondly, we introduced the time degree function reflecting the decision makers? subjective time preference, and established a multi-objective programming model to obtain time weights; then we used dynamic intuitionistic fuzzy weighted geometric (DIFWG) operator to integrate different time periods of the intuitionistic fuzzy decision matrices; the VIKOR method is used in ranking solutions that takes account of group effectiveness maximization and individual regret minimization, and obtained the optimal scheme that is closet to ideal solution; finally, the feasibility and effectiveness of the proposed method is verified by the example of a technology innovation alliance partner selection.
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Yang, Anrong, Zigang Zhang, Yishi Zhang, and Dunliang Chen. "Gap Minimization for Peer-Evaluation in DEA Cross-Efficiency." Journal of Applied Mathematics 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/453749.
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Cross-efficiency evaluation is an effective and widely used method for ranking decision making units (DMUs) in data envelopment analysis (DEA). Gap minimization criterion is introduced in aggressive and benevolent cross-efficiency methods to avoid possible extreme efficiency from peer-evaluation and to get equitable results. On the basis of this criterion, a weighted cross-efficiency method with similarity distance that, respectively, considers the aggressive and the benevolent formulations is proposed to determine cross-efficiency. The weights of the cross-evaluation determined by this method are positively influenced by self-evaluation and thus are propitious to resolving conflict. Numerical demonstration reveals the feasibility of the proposed method.
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Zhao, Chun Na, Yu Zhao, Li Ming Luo, and Ying Shun Li. "Course Evaluation Method Based on Fractional Correlation Distance and AHP." Advanced Materials Research 204-210 (February 2011): 512–17. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.512.
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Course evaluation is an important and necessary means to improve the level of course. A new course evaluation method based on fractional grey relational distance and analytic hierarchy process (AHP) is proposed in this paper. Firstly, the proportion of the different influence factors can be determined through constructing judging-matrix and calculating-back-to-one and dealing with the checkout of coherence. Secondly, qualitative evaluation indicators are quantified by fractional-order system, and quantitative indicators are processed by idealization and normalization. And then association coefficient is defined. Finally, correlation distance degree is proposed. The new similarity degree reflects the relatedness and the different shape among a selected scheme, the ideal solution and negative ideal solution. Through the application to actual course assessment instance, the results show its practicability and effectiveness.
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Yokozuka, Masashi, and Osamu Matsumoto. "A Reasonable Path Planning via Path Energy Minimization." Journal of Robotics and Mechatronics 26, no. 2 (April 20, 2014): 236–44. http://dx.doi.org/10.20965/jrm.2014.p0236.
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This paper presents a path planning method by path energy minimizing that enables mobile robots to move smoothly in the real world with optimizing path shape for shortest distance or minimum curvature. It also enables robots to travel safely toward a destination because pedestrian motion prediction is embedded in path planning. This path planning method is based on problems experienced in a robot competition called Tsukuba Challenge. The problems involved nonsmooth motion arising from finite path patterns in A* algorithm, stuck motion arising from frequently path switching, and near misses arising from nonpredictive planning. Our path planning method minimizes pathshape energy defined as the connection between path points. Minimizing energy provides smooth paths and avoids path switching. We propose a path planning method with prediction of dynamic obstacle motion embedded to avoid near misses. Experimental results showed improvements in solving these problems.
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Wang, Ting, and Li Feng Li. "Decision Based on Fuzzy Multi-Objective Programming Method of High-Tech Investment Portfolio." Key Engineering Materials 474-476 (April 2011): 1961–65. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.1961.
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The expected rate of earnings and risk of high-tech projects are very fuzzy, and investors hope to get the expected rate of earnings maximization and risk minimization. Therefore, this paper establishes the model of fuzzy multi-objective programming method to select an optimal portfolio scheme. On the one hand, the objectives risk can be scattered, on the other hand investors can get ideal earnings. The example shows that this method to solve problems of portfolio investment decision is feasible and effective.
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Lu, Yaean-Jye, John Z. Luh, and Alan K. Yep. "Using queue distance to supplement traffic signal timing design." Canadian Journal of Civil Engineering 17, no. 4 (August 1, 1990): 652–58. http://dx.doi.org/10.1139/l90-074.
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A common approach in traffic signal timing design at isolated intersections is to assume homogeneous traffic flows and ideal geometric conditions, and then to apply adjustment factors so that variations from the ideal conditions are considered. Since the ideal and adjustment values are usually developed from empirical field data, the final result may not accurately reflect the true local situation. Fine tuning, primarily based on personal judgment, is therefore almost always required because local conditions differ from study conditions. This paper presents a method which relies solely on an empirical traffic factor, namely queue distance, to determine the green time. Field surveys at three intersections were conducted to establish the equations used in this method. The coefficients of the equations are interpreted. The applications of this method to supplement the fine tuning are presented. The potential application of this method on traffic responsive control is also proposed. Key words: traffic signal, queue, regression analysis, pretimed signal, traffic responsive control.
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Jiang, Wen, Meijuan Wang, Xinyang Deng, and Linfeng Gou. "Fault diagnosis based on TOPSIS method with Manhattan distance." Advances in Mechanical Engineering 11, no. 3 (March 2019): 168781401983327. http://dx.doi.org/10.1177/1687814019833279.
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Fault diagnosis is important for the maintenance of machinery equipment. Due to the randomness and fuzziness of fault, the relationship between fault types and their characteristics are complicated. Therefore, the determination of fault type is a challenging part of machinery fault diagnosis with the traditional method. To tackle this problem, a fault diagnosis approach based on the technique for order performance by similarity to ideal solution with Manhattan distance is presented in this article. First, the similarity measure between the fault model and the detection sample is constructed based on the Manhattan distance. Then, the similarity is transformed into intuitionistic fuzzy set and the generated intuitionistic fuzzy set is fused by the intuitionistic fuzzy weighted averaging operator. On this basis, the technique for order performance by similarity to the ideal solution approach is utilized to obtain the final rank to ascertain the fault type. The proposed method can handle an intricate relationship between multiple fault types and their various fault characteristics and better express uncertain information. Finally, a fault diagnosis example of the machine rotor and comparative study are conducted to illustrate the application and the effectiveness of the proposed method.
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Fitrianingsih, Fitrianingsih, Sarifuddin Madenda, Ernastuti Ernastuti, Suryarini Widodo, and Rodiah Rodiah. "Cursive Handwriting Segmentation using Ideal Distance Approach." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (October 1, 2017): 2863. http://dx.doi.org/10.11591/ijece.v7i5.pp2863-2872.
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Offline cursive handwriting becomes a major challenge due to the huge amount of handwriting varieties such as slant handwriting, space between words, the size and direction of the letter, the style of writing the letter and handwriting with contour similarity on some letters. There are some steps for recursive handwriting recognition. The steps are preprocessing, morphology, segmentation, features of letter extraction and recognition. Segmentation is a crucial process in handwriting recognition since the success of segmentation step will determine the success level of recognition. This paper proposes a segmentation algorithm that segment recursive handwriting into letters. These letters will form words using a method that determine the intersection cutting point of image recursive handwriting with an ideal image distance. The ideal distance of recursive handwriting image is an ideal distance segmentation point in order to avoid the cutting of other letter’s section. The width and height of images are used to determine the accurate segmentation point. There were 999 recursive handwriting input images taken from 25 researchers used for this study. The images used are the images obtained from preprocessing step. Those are the images with slope correction. This study used Support Vector Machine (SVM) to recognize recursive handwriting. The experiments show the proposed segmentation algorithm able to segment the image precisely and have 97% success recognizing the recursive handwriting.
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Sianturi, Hotman Jandri Vay, and Lince Tomoria Sianturi. "Sistem Pendukung Keputusan Untuk Memilih BTS (Base Transceiver Station) Service Terburuk dengan Menerapkan Fuzzy MADM." Building of Informatics, Technology and Science (BITS) 3, no. 1 (June 30, 2021): 26–30. http://dx.doi.org/10.47065/bits.v3i1.164.
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Information about the performance of a BTS (Base Transceiver Station) is needed to help improve a Network service. But in the selection of a good or bad BTS (Base Transceiver Station) it can be caused by several factors such as Transmission, Power, and Celldown BTS. Therefore we need a system that can provide recommendations using the right method, here are the decision support system methods including Fuzzy Multiple Attribute Decision Making TOPSIS. The TOPSIS method uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution from a geometric point of view using Euclidean distance (distance between two points) to determine the relative proximity of an alternative with the optimal solution . Positive ideal solutions are defined as the sum of all the best values that can be achieved for each attribute, while the negative-ideal solution consists of all the worst values achieved for each attribute. while the negative-ideal solution consists of all the worst values achieved for each attribute.
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Rytsar, Bohdan Ye, and Artem O. Belovolov. "A New Method of the Logical Functions Minimization in the Polynomial Set-Theoretical Format. «Handshaking» Procedure." Control Systems and Computers, no. 1 (291) (April 2021): 03–14. http://dx.doi.org/10.15407/csc.2021.01.003.
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A new minimization method of logic functions of n variables in polynomial set-theoretical format has been considered. The method based on the so-called “handshaking” procedure. This procedure reflects the iterative polynomial extension of two conjuncterms of different ranks, the Hamming distance between which can be arbitrary. The advantages of the suggested method are illustrated by the examples.
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Tan, Qian-Yun, Cui-Ping Wei, Qi Liu, and Xiang-Qian Feng. "The Hesitant Fuzzy Linguistic TOPSIS Method Based on Novel Information Measures." Asia-Pacific Journal of Operational Research 33, no. 05 (October 2016): 1650035. http://dx.doi.org/10.1142/s0217595916500354.
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Hesitant fuzzy linguistic term sets (HFLTSs) have attracted lots of attention recently due to their distinguished power and efficiency for dealing with multi-criteria decision making. To extend the applicability of HFLTSs, this paper first presents a more concise comparison formula of hesitant fuzzy linguistic term sets based on probability criterion of uniform distribution and develops novel distance measures considering the hesitance degree. Next, an aggregation scheme is designed to integrate OWD measure into the TOPSIS analysis procedure, in which we calculate different criterion weights according to the distance between criterion values and positive and negative ideal solutions. The weighted distances between the alternatives and positive and negative ideal solutions are calculated. Then the relative closeness degree to the positive ideal solution is calculated to rank all alternatives. Finally, an example is given to illustrate the capabilities and validation of the proposed algorithm.
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Erpolat Taşabat, Semra. "A Novel Multicriteria Decision-Making Method Based on Distance, Similarity, and Correlation: DSC TOPSIS." Mathematical Problems in Engineering 2019 (April 30, 2019): 1–20. http://dx.doi.org/10.1155/2019/9125754.
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Decision-making, briefly defined as choosing the best among the possible alternatives within the possibilities and conditions available, is a far more comprehensive process than instant. While in the decision-making process, there are often a lot of criteria as well as alternatives. In this case, methods referred to as Multicriteria Decision-Making (MCDM) are applied. The main purpose of the methods is to facilitate the decision-maker's job, to guide the decision-maker and help him to make the right decisions if there are too many options. In cases where there are many criteria, effective and useful decisions have been taken for granted at the beginning of the 1960s for the first time and supported by day-to-day work. A variety of methods have been developed for this purpose. The basis of some of these methods is based on distance measures. The most known method in the literature based on the concept of distance is, of course, a method called Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In this study, a new MCDM method that uses distance, similarity, and correlation measures has been proposed. This new method is shortly called DSC TOPSIS to include the initials of distance, similarity, and correlation words, respectively, prefix of TOPSIS name. In the method, Euclidean was used as distance measure, cosine was used as similarity measure, and Pearson correlation was used as relation measure. Using the positive ideal and negative-ideal values obtained from these measures, respectively, a common positive ideal value and a common negative-ideal value were obtained. Afterward DSC TOPSIS is discussed in terms of standardization and weighting. The study also proposed three different new ranking indexes from the ranking index used in the traditional TOPSIS method. The proposed method has been tested on the variables showing the development levels of the countries that have a very important place today. The results obtained were compared with the Human Development Index (HDI) value developed by the United Nations.
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Liu, Ruiwei, Siqi Hao, Yaping Zhang, Chonghang Xu, Wenjing Li, and Yunrui Mo. "A Novel Strategic Aircraft Track Planning Method Considering Conflict Probability." Aerospace 9, no. 12 (December 19, 2022): 848. http://dx.doi.org/10.3390/aerospace9120848.
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Generally, air track planning is conducted in real time and takes modified track distance minimization as objective. Next-generation air transport systems provide aircrafts with more flexibility in track planning and more responsibilities in self-separation, which present a great challenge for aircraft optimal track planning, especially in some high-density airspaces and some complex conflict scenarios. This paper proposes a novel aircraft track planning method by taking aircraft conflict probability into consideration. First, the concepts of aircraft potential motion space and the estimation method for aircraft conflict probability is introduced. Then, taking conflict probability minimization as the objective, the classical ant colony algorithm (ACA) algorithm is improved to solve the model. Finally, an experimental study is conducted to illustrate the proposed method. Results show that the proposed method is able to provide a scientific and effective track planning approach considering the potential conflict probability of aircrafts, which is able to provide fundamental to the safety of entire air transport system.
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Henry-Edwards, A., and M. Tomczak. "Remote detection of water property changes from a time series of oceanographic data." Ocean Science 2, no. 1 (March 8, 2006): 11–18. http://dx.doi.org/10.5194/os-2-11-2006.
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Abstract. A water mass analysis method based on a constrained minimization technique is developed to derive water property changes in water mass formation regions from oceanographic station data taken at significant distance from the formation regions. The method is tested with two synthetic data sets, designed to mirror conditions in the North Atlantic at the Bermuda BATS time series station. The method requires careful definition of constraints before it produces reliable results. It is shown that an analysis of the error fields under different constraint assumptions can identify which properties vary most over the period of the observations. The method reproduces the synthetic data sets extremely well if all properties other than those that are identified as undergoing significant variations are held constant during the minimization.
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Henry-Edwards, A., and M. Tomczak. "Remote detection of water property changes from a time series of oceanographic data." Ocean Science Discussions 2, no. 4 (August 30, 2005): 399–415. http://dx.doi.org/10.5194/osd-2-399-2005.
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Abstract. A water mass analysis method based on a constrained minimization technique is developed to derive water property changes in water mass formation regions from oceanographic station data taken at significant distance from the formation regions. The method is tested with two synthetic data sets, designed to mirror conditions in the North Atlantic at the Bermuda BATS time series station. The method requires careful definition of constraints before it produces reliable results. It is shown that an analysis of the error fields under different constraint assumptions can identify which properties vary most over the period of the observations. The method reproduces the synthetic data sets extremely well if all properties other than those that are identified as undergoing significant variations are held constant during the minimization.
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Kapou, Vasiliki, Stavros T. Ponis, George Plakas, and Eleni Aretoulaki. "An Innovative Layout Design and Storage Assignment Method for Manual Order Picking with Respect to Ergonomic Criteria." Logistics 6, no. 4 (December 6, 2022): 83. http://dx.doi.org/10.3390/logistics6040083.
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Background: This paper aims to improve the overall performance of manual warehouse Order Picking (OP) processes by proposing an innovative method for designing a picking area layout, and introducing a storage assignment strategy with respect to ergonomics and workers’ physical fatigue. Methods: The proposed method categorizes the available picking slots based on size and ABC analysis. Ιt takes into consideration a set of ergonomic constraints pertinent to the rack heights and travel distance restrictions for each slot type, leading to the assignment of a location to each slot type based on its individual characteristics. In doing so, the proposed method introduces an innovative ‘flame-shape’ aisle layout. Finally, the products are assigned to their optimal locations, targeting OP time minimization, balanced workload allocation, and ergonomics optimization through a ranking system measuring the ‘difficulty’ of retrieving the products based on their weight, popularity, and slot location. Results: The proposed method led to a productivity rise of 14.9% along with a significant decrease of the ‘difficulty’ index, by 31%. Conclusions: The results prove that a prominent performance improvement can be achieved when both travel distance and manual workload minimization are targeted for determining the picking area layout and storage design.
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Wang, Shihua, Yanmin Liu, Kangge Zou, Nana Li, and Yaowei Wu. "Multiobjective Particle Swarm Optimization Based on Ideal Distance." Discrete Dynamics in Nature and Society 2022 (April 11, 2022): 1–16. http://dx.doi.org/10.1155/2022/3515566.
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Recently, multiobjective particle swarm optimization (MOPSO) has been widely used in science and engineering, however how to effectively improve the convergence and distribution of the algorithm has always been a hot research topic on multiobjective optimization problems (MOPs). To solve this problem, we propose a multiobjective particle swarm optimization based on the ideal distance (IDMOPSO). In IDMOPSO, the adaptive grid and ideal distance are used to optimize and improve the selection method of global learning samples and the size control strategy of the external archive, and the fine-tuning parameters are introduced to adjust particle flight in the swarm dynamically. Additionally, to prevent the algorithm from falling into a local optimum, the cosine factor is introduced to mutate the position of the particles during the exploitation and exploration process. Finally, IDMOPSO, several other popular MOPSOs and MOEAs were simulated on the benchmarks functions to test the performance of the proposed algorithm using IGD and HV indicators. The experimental results show that IDMOPSO has the better convergence, diversity, and excellent solution ability compared to the other algorithms.
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Oviedo, Harry. "Proximal Point Algorithm with Euclidean Distance on the Stiefel Manifold." Mathematics 11, no. 11 (May 23, 2023): 2414. http://dx.doi.org/10.3390/math11112414.
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In this paper, we consider the problem of minimizing a continuously differentiable function on the Stiefel manifold. To solve this problem, we develop a geodesic-free proximal point algorithm equipped with Euclidean distance that does not require use of the Riemannian metric. The proposed method can be regarded as an iterative fixed-point method that repeatedly applies a proximal operator to an initial point. In addition, we establish the global convergence of the new approach without any restrictive assumption. Numerical experiments on linear eigenvalue problems and the minimization of sums of heterogeneous quadratic functions show that the developed algorithm is competitive with some procedures existing in the literature.
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Xia, Meimei, and Zeshui Xu. "A Novel Method for Fuzzy Multi-Criteria Decision Making." International Journal of Information Technology & Decision Making 13, no. 03 (May 2014): 497–519. http://dx.doi.org/10.1142/s0219622014500205.
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To determine the weight vector and to aggregate the individual opinions are necessary steps in the classical methods for multi-criteria group decision-making problems in which the weight vectors of the decision makers and the criteria are incompletely known. In this paper, we propose a simple but efficient approach which can avoid these steps by establishing some optimal models. To get the optimal group decision matrix, we first propose two kinds of models among which the former focuses on minimizing the deviations between individual decision matrix and the ideal group one, while the latter aims at minimizing the deviations between the estimated group opinion and the ideal group one. To get the overall performances of alternatives, another two types of models are further established, one of which is to minimize the distance between the evaluation value under each criterion and the ideal overall value for each alternative, and the other is to minimize the distance between the estimated overall value and the ideal overall one. The proposed models can be used to deal with group decision-making under intuitionistic fuzzy, interval-valued fuzzy or other fuzzy environments, and can also provide the decision makers more choices by containing the parameter which can be assigned different values according to different actual situations. Several examples illustrate the practicability of the proposed methods.
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Lee, Sunghae, and Sangchul Kim. "A Method for Assigning Clients to Servers for the Minimization of Client-Server Distance Deviation." Journal of Korea Game Society 16, no. 3 (June 30, 2016): 97–108. http://dx.doi.org/10.7583/jkgs.2016.16.3.97.
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Chan, Wesley P., Matthew K. X. J. Pan, Elizabeth A. Croft, and Masayuki Inaba. "An Affordance and Distance Minimization Based Method for Computing Object Orientations for Robot Human Handovers." International Journal of Social Robotics 12, no. 1 (April 15, 2019): 143–62. http://dx.doi.org/10.1007/s12369-019-00546-7.
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Handoko, Henrycus Baik. "Decision Support System for Determination of Water Supply Distribution Decisions Using the Technique for Order Preference Method by Similarity to Ideal Solution (TOPSIS)." Jurnal Mandiri IT 10, no. 1 (July 30, 2021): 14–22. http://dx.doi.org/10.35335/mandiri.v10i1.99.
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The Water Supply Decision Support System is a computer-based information system that can be used to help support the quality of human life in terms of providing clean water. In this system, the results will be in the form of priority decisions for the provision of clean water for each candidate area. In the Social Service Office of Sragen Regency itself, there are criteria in determining decisions according to the results of the proposals submitted by each regional candidate including the number of families who need clean water (KK), the number of people in each region (SOUL), the number of water drops in each region (TANK), and the number of hamlets that need clean water in each area (DUKUH). TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is the method used in this system, determine the results of relative proximity to the ideal solution so that it can produce priority values from several areas. This method was chosen because it considers the distance to the positive ideal solution and the distance to the negative ideal solution by taking relative proximity to the positive ideal solution. Based on the comparison to the relative distances, an alternative priority arrangement can be reached. Based on the comparison to the relative distances, an alternative priority arrangement can be reached. From the results obtained, it can be used to help procure clean water to areas that meet priorities, and its nature only helps to find priority values according to relative proximity to the ideal solution and is not the final goal for decision making. This method was chosen because it considers the distance to the positive ideal solution and the distance to the negative ideal solution by taking relative proximity to the positive ideal solution. Based on the comparison to the relative distances, an alternative priority arrangement can be reached. From the results obtained, it can be used to help procure clean water to areas that meet priorities, and its nature only helps to find priority values according to relative proximity to the ideal solution and is not the final goal for decision making.