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Journal articles on the topic 'Multicriteria Optimization'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 June 2024

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1

Craft, David, Dualta McQuaid, Jeremiah Wala, Wei Chen, Ehsan Salari, and Thomas Bortfeld. "Multicriteria VMAT optimization." Medical Physics 39, no. 2 (January 12, 2012): 686–96. http://dx.doi.org/10.1118/1.3675601.

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2

Beaulieu, Luc, Hania Al-Hallaq, Benjamin S. Rosen, and David J. Carlson. "Multicriteria Optimization in Brachytherapy." International Journal of Radiation Oncology*Biology*Physics 114, no. 2 (October 2022): 177–80. http://dx.doi.org/10.1016/j.ijrobp.2022.05.022.

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3

Murdoch, Dr Tim. "Multicriteria optimization and engineering." Materials & Design 16, no. 2 (January 1995): 120–21. http://dx.doi.org/10.1016/0261-3069(95)90021-7.

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4

Lupşa, Liana, and Nicolae Popovici. "Generalized unimodal multicriteria optimization." Journal of Numerical Analysis and Approximation Theory 35, no. 1 (February 1, 2006): 65–70. http://dx.doi.org/10.33993/jnaat351-1012.

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The aim of this paper is to characterize the sets of weakly-efficient solutions and efficient solutions for multicriteria optimization problem involving generalized unimodal objective functions. An implementable algorithm which completely determines these sets is given for the particular framework of discrete feasible domains.

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5

Statnikov, Roman, Josef Matusov, Kirill Pyankov, and Alexander Statnikov. "Multicriteria Optimization of Cellular Networks." Open Journal of Optimization 02, no. 03 (2013): 53–60. http://dx.doi.org/10.4236/ojop.2013.23008.

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6

Popovici *, Nicolae. "Pareto reducible multicriteria optimization problems." Optimization 54, no. 3 (June 2005): 253–63. http://dx.doi.org/10.1080/02331930500096213.

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7

La Torre, Davide, and Nicolae Popovici. "Arcwise cone-quasiconvex multicriteria optimization." Operations Research Letters 38, no. 2 (March 2010): 143–46. http://dx.doi.org/10.1016/j.orl.2009.11.003.

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8

Chen, Huixiao, David L. Craft, and David P. Gierga. "Multicriteria optimization informed VMAT planning." Medical Dosimetry 39, no. 1 (2014): 64–73. http://dx.doi.org/10.1016/j.meddos.2013.10.001.

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9

Fliege, J., and L. N. Vicente. "Multicriteria Approach to Bilevel Optimization." Journal of Optimization Theory and Applications 131, no. 2 (November 8, 2006): 209–25. http://dx.doi.org/10.1007/s10957-006-9136-2.

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10

Frangopol, Dan M. "Multicriteria reliability-based structural optimization." Structural Safety 3, no. 1 (October 1985): 23–28. http://dx.doi.org/10.1016/0167-4730(85)90004-9.

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11

Adler, Christoph, Danica Siedenberg, and Matthias Töns. "Multicriteria Optimization of Electric Drivetrains." ATZ worldwide 122, no. 3 (February 28, 2020): 40–45. http://dx.doi.org/10.1007/s38311-019-0189-x.

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12

Gutjahr, Walter J., and Pamela C. Nolz. "Multicriteria optimization in humanitarian aid." European Journal of Operational Research 252, no. 2 (July 2016): 351–66. http://dx.doi.org/10.1016/j.ejor.2015.12.035.

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13

Klamroth, Kathrin, Jørgen Tind, and Margaret M. Wiecek. "Unbiased approximation in multicriteria optimization." Mathematical Methods of Operations Research (ZOR) 56, no. 3 (January 1, 2003): 413–37. http://dx.doi.org/10.1007/s001860200217.

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14

Angell, T. S., and A. Kirsch. "Multicriteria optimization in antenna design." Mathematical Methods in the Applied Sciences 15, no. 9 (December 1992): 647–60. http://dx.doi.org/10.1002/mma.1670150905.

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15

Kochkarov, Rasul. "Multicriteria Optimization Problem on Prefractal Graph." Mathematics 10, no. 6 (March 14, 2022): 930. http://dx.doi.org/10.3390/math10060930.

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Even among single-criteria discrete problems, there are NP-hard ones. Multicriteria problems on graphs in many cases become intractable. Currently, priority is given to the study of applied multicriteria problems with specific criteria; there is no classification of criteria according to their type and content. There are few studies with fuzzy criteria, both weight and topological. Little attention is paid to the stability of solutions, and this is necessary when modeling real processes due to their dynamism. It is also necessary to study the behavior of solution sets for various general and individual problems. The theory of multicriteria optimization is a rather young branch of science and requires the development of not only particular methods, but also the construction of a methodological basis. This is also true in terms of discrete graph-theoretic optimization. In this paper, we propose to get acquainted with multicriteria problems for a special class of prefractal graphs. Modeling natural objects or processes using graphs often involves weighting edges with many numbers. The author proposes a general formulation of a multicriteria problem on a multi-weighted prefractal graph; defines three sets of alternatives—Pareto, complete and lexicographic; and proposes a classification of individual problems according to the set of feasible solutions. As an example, we consider an individual problem of placing a multiple center with two types of weight criteria and two types of topological ones. An algorithm with estimates of all criteria of the problem is proposed.

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16

Temis, Y. M., and D. A. Yakushev. "Multicriteria optimal design turbomachine disk." Izvestiya MGTU MAMI 6, no. 2-2 (March 20, 2012): 330–36. http://dx.doi.org/10.17816/2074-0530-68557.

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Modern concepts of using optimization technologies for structural design are considered. Several approaches of optimization problems for compressor disk are considered. The problem of total weight minimization under certain stress and stiffness constraints is investigated. All results were obtained using developed FE analysis program connected with SQP optimization procedure.

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17

Farina, M., and P. Amato. "Linked interpolation-optimization strategies for multicriteria optimization problems." Soft Computing 9, no. 1 (October 13, 2003): 54–65. http://dx.doi.org/10.1007/s00500-003-0334-7.

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18

Tian, Zhiyong, Yaxin Wang, and Qingping Xue. "Optimization of Urban Landscape Planning and Layout under Multicriteria Constraints." Mathematical Problems in Engineering 2022 (August 24, 2022): 1–9. http://dx.doi.org/10.1155/2022/2991188.

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The layout and planning of urban landscape has a strong correlation with urban land utilization rate and ecological environment index. Urban landscape architects have a hard time dealing with these interrelated factors. This study uses a multicriteria constraint algorithm to optimize the relevant factors in urban landscape layout and planning. The convolutional long short-term memory (ConvLSTM) method was used to extract temporal features for urban landscape layout and planning tasks. Compared with the multicriteria algorithm without constraints, the multicriteria algorithm with constraints can better optimize the layout and planning tasks of urban landscape, and the maximum error of this method is only 1.96%. At the same time, the distribution of errors is more uniform under the multicriteria constraints, and it is all within 2%. The fusion of the multicriteria constraint algorithm and the ConvLSTM algorithm can better predict the relevant factors of the urban landscape layout, and the linear correlation coefficients of the three relevant factors have reached a high standard.

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19

Ivanchenko, Hryhorii, Oleksandr Koshevyi, and Oleksandr Koshevyi. "Numerical implementation of multicriteria parametric optimization of minimum surface shell on a square contour under thermforce loading." Strength of Materials and Theory of Structures, no. 109 (November 11, 2022): 50–65. http://dx.doi.org/10.32347/2410-2547.2022.109.50-65.

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The article considers the numerical study of the multicriteria parametric optimization of the minimum surface shell on the square contour under thermoforce loading. The mathematical algorithm for solving the problem of multicriteria parametric optimization of minimal surfaces shellsis described: the necessary output data are given, which target functions can be used, design variables and constraints are described. The influence of initial data on the numerical study of multicriteria parametric optimization was shown. The calculation of necessary components and matrices for multicriteria parametric optimization of minimal surfaces shells, as well as methods of its simplification, depending on the initial data was made. Was shown in which cases the algorithm is executed successfully, and where it was necessary to return to change the initial parameters. The sensitivity analysis of multi-criteria parametric optimization of minimal surfaces shells is presented. In article reveals the inner essence of the structure's work while the optimization calculation was done. Work with internal forces and stresses, the connection with the finite element method and its stiffness matrix were made. The process and methodology of setting ofthermoforce loadare revealed.All initial parameters, as well as how the load works with multicriteria parametric optimization are shown. The numerical experiment made it possible to reduce the weight of minimum surface shell on the square contour by 5%, and the movement along the coordinate axes by 38%, which are the target functions of multicriteria parametric optimization. Redistribution of the thickness of the minimum surface shell on the square contour from 1 mm to 31 mm was realized. The interaction of the objective functions is shown - they conflict, as well as the graphs of changes in Mises stresses, shear stresses and strain energy, which makes it possible to reveal the internal processes of multi-criteria parametric optimization of the minimum surface shell on a square contour. Subject of this study is an interesting applied problem for construction mechanics, as it is the first time to display the application of two types of optimization on one research object.

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20

Kim, Ki Sung, Kyung Su Kim, and Ki Sup Hong. "Grillage Optimization with Multiple Objectives." Key Engineering Materials 306-308 (March 2006): 517–22. http://dx.doi.org/10.4028/www.scientific.net/kem.306-308.517.

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The structural design problems are acknowledged to be commonly multicriteria in nature. The various multicriteria optimization methods are reviewed and the most efficient and easy-to-use Pareto optimal solution methods are applied to structural optimization of grillages under lateral uniform load. The result of the study shows that Pareto optimal solution methods can easily be applied to structural optimization with multiple objectives, and the designer can have a choice from those Pareto optimal solutions to meet an appropriate design environment.

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21

Matusov, Leonid B. "The vector optimization and modeling of a technical systems." MATEC Web of Conferences 224 (2018): 04020. http://dx.doi.org/10.1051/matecconf/201822404020.

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The construction a feasible solution set with a given accuracy is a main problem in multicriteria optimization and modeling. In order to construct the feasible solution set, a method called the Parameter Space Investigation has been created and successfully integrated into various fields of industry, science, and technology. Multicriteria modeling (identification) is a new direction that is of great value in applications. In the most common usage, the term “identification” means construction of the mathematical model of a system and determination of the parameters (design variables) of the model. The construction a feasible solution set with a given accuracy is a common way for solving multicriteria optimization and modeling problems. The issues of the estimation of the Parameter Space Investigation method convergence rate, the approximation of the feasible solution set are described. Besides these, the multicriteria identification problems of mechanical systems are discussed too.

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22

Hoppe, S., R. Rached, C. Fonteix, and F. Pla. "MULTICRITERIA OPTIMIZATION OF NANOSTRUCTURED POLYAMIDE BLENDS." IFAC Proceedings Volumes 39, no. 4 (2006): 459–65. http://dx.doi.org/10.3182/20060522-3-fr-2904.00074.

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23

Craven, B. D. "On sensitivity analysis for multicriteria optimization." Optimization 19, no. 4 (January 1988): 513–23. http://dx.doi.org/10.1080/02331938808843370.

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24

Stadler, W. "Caveats and Boons of Multicriteria Optimization." Computer-Aided Civil and Infrastructure Engineering 10, no. 4 (July 1995): 291–99. http://dx.doi.org/10.1111/j.1467-8667.1995.tb00291.x.

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25

Akhmadiev, F. G. "Some problems of multicriteria process optimization." Theoretical Foundations of Chemical Engineering 48, no. 5 (September 2014): 574–82. http://dx.doi.org/10.1134/s0040579514050145.

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26

Chlopinska, Ewelina, and Maciej Gucma. "Multicriteria Optimization Method of LNG Distribution." TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation 14, no. 2 (2020): 493–97. http://dx.doi.org/10.12716/1001.14.02.30.

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27

Lotov, A. V. "Multicriteria optimization of convex dynamical systems." Differential Equations 45, no. 11 (November 2009): 1669–80. http://dx.doi.org/10.1134/s0012266109110123.

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28

Fliege, Jörg, and Benar Fux Svaiter. "Steepest descent methods for multicriteria optimization." Mathematical Methods of Operations Research (ZOR) 51, no. 3 (August 17, 2000): 479–94. http://dx.doi.org/10.1007/s001860000043.

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29

Nelson, Sigurd A., Matthew B. Parkinson, and Panos Y. Papalambros. "Multicriteria Optimization in Product Platform Design." Journal of Mechanical Design 123, no. 2 (January 1, 2000): 199–204. http://dx.doi.org/10.1115/1.1355775.

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A product platform is a set of common components, modules or parts from which a stream of derivative products can be created. Product platform design requires selection of the shared parts and assessment of the potential sacrifices in individual product performance that result from parts sharing. A multicriteria optimization problem can be formulated to study such decisions in a quantitative manner at the product performance level. Studying the Pareto sets that correspond to various derivative products leads to a systematic methodology for design decision making. Design of a nail gun platform is used to illustrate the concepts presented.

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30

Joswig, Michael, and Georg Loho. "Monomial Tropical Cones for Multicriteria Optimization." SIAM Journal on Discrete Mathematics 34, no. 2 (January 2020): 1172–91. http://dx.doi.org/10.1137/17m1153066.

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31

Henig, Mordechai I. "The domination property in multicriteria optimization." Journal of Mathematical Analysis and Applications 114, no. 1 (February 1986): 7–16. http://dx.doi.org/10.1016/0022-247x(86)90061-2.

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32

Carraway, Robert L., Thomas L. Morin, and Herbert Moskowitz. "Generalized dynamic programming for multicriteria optimization." European Journal of Operational Research 44, no. 1 (January 1990): 95–104. http://dx.doi.org/10.1016/0377-2217(90)90318-6.

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33

Ohkubo, Sadaji, and P. B. R. Dissanayake. "Multicriteria fuzzy optimization of structural systems." International Journal for Numerical Methods in Engineering 45, no. 2 (May 20, 1999): 195–214. http://dx.doi.org/10.1002/(sici)1097-0207(19990520)45:2<195::aid-nme588>3.0.co;2-x.

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34

Hellwig, Klaus. "Tradeoff oriented solutions in multicriteria optimization." Annals of Operations Research 164, no. 1 (April 15, 2008): 111–14. http://dx.doi.org/10.1007/s10479-008-0345-y.

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35

Koshevyi, Oleksandr, Oleksandr Koshevyi, and Liudmyla Grigoryеva. "Numerical implementation of multicriteria parametric optimization of minimum surface shell on a rectangular contour under the rmalloading." Strength of Materials and Theory of Structures, no. 108 (May 30, 2022): 309–24. http://dx.doi.org/10.32347/2410-2547.2022.108.309-324.

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The article considers the numerical study of multicriteria optimization of the minimum surface shell of a rectangular contour taking into account the thermal load. The authors cover the theoretical formulation of multicriteria parametric optimization. A method of constructing this minimal surface on a rectangular contour is described. The specifics of the issuance of thermal power load in the optimization calculation, which is in all initial indicators and coefficients. The types of work of target functions are shown, namely: under what conditions they conflict, under what conditions they consolidate, under what conditions they are independent of each other. The numerical study uses the author's software, which allows in automatic mode a multicriteria optimization calculation with target functions - weight and Mises stress, design variables - thickness from 1 to 200 mm, presented as a Mises voltage of 240 MPa. The result showed that the target functions of the conflict change, but the weight decreases by 20%, and the Mises voltage decreases by 37% of the elements. From the graph of the change of objective functions according to the optimal height, what is the point for the objective functions - weight and stress according to Mises is absence. The overall purpose of the study shows the possibility of using authoring software to use two types of optimization: optimization of shapes in the form of these minimum surface parameters on rectangular and multicriteria optimization together on the object under study, which is interesting and applied research in structural mechanics.

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36

Bosov, O. O., H. M. Kodola, and L. M. Savchenko. "VECTOR OPTIMIZATION FOR THE TWO INDICATORS." Science and Transport Progress, no. 17 (August 25, 2007): 134–38. http://dx.doi.org/10.15802/stp2007/17598.

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37

Bowen, Gong, and Lin Ciyun. "A Personalized Urban Multicriteria Shortest Path Stochastic Optimization Algorithm." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/987358.

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Drivers’ route choice behavior is usually personalized and multicriteria in practice. Therefore, the urban shortest path problem is the personalized urban multicriteria shortest path (PUMSP) problem. However, the solutions of the PUMSP problem are difficult to meet the drivers’ travel habits in the state of the art. To solve this problem, first, a new stochastic optimization algorithm based on the iterative calculation of a valid route set is proposed in this paper. The effective and reasonable path searching mechanism is designed based on drivers’ route choice habits. Then, the evaluation method of calculation results is given. The comparative experimental results with the genetic algorithm show that the proposed algorithm has reached better results in the evaluation parameters and computing time. The experimental results also demonstrate that it is meaningful to consider drivers’ travel law in the personalized urban multicriteria shortest path algorithm design for avoiding obtaining impractical routes solutions.

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38

Ray, Tapabrata, and Om Prakash Sha. "Multicriteria Optimization Model for a Containership Design." Marine Technology and SNAME News 31, no. 04 (October 1, 1994): 258–68. http://dx.doi.org/10.5957/mt1.1994.31.4.258.

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This paper describes a multicriteria optimization approach to ship design. The method incorporates accepted naval architectural estimation methods, a decision system handler and a nonlinear optimization tool. It allows the designer to identify different objectives, define prescribed limits on the design variables or define constraints on the design. The decision system identifies the weightages corresponding to different objectives based on the relative importance of the objectives using multi-attribute decision-making methods. The advantage of using optimization techniques along with a decision system handler allows the designer to develop new designs, while considering various interactions within the system, in a shorter time span. The proposed approach is illustrated by its application to a containership design. The effect of the weightages associated with the different objectives on the overall design is shown in the case studies.

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39

Chen, Jianda, Xingwei Dai, and Xingwen Cai. "Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method." Adsorption Science & Technology 2022 (October 8, 2022): 1–10. http://dx.doi.org/10.1155/2022/9604936.

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This paper uses SketchUp and OpenStudio to design and optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. By establishing a basic model, the performance parameters such as insulation thickness, typical outer window, window-to-wall ratio, and their contribution rates within the threshold range are optimized for energy conservation; simulate the energy consumption of the determined multiperformance parameter combination scheme, select the most energy-saving scheme, and calculate its energy-saving contribution rate; calculate the life cycle cost of the above schemes, select the scheme with the lowest cost, and analyze its economic benefits; select energy-saving cost and economic benefit, and calculate energy-saving contribution rate and economic benefit. Finally, through the comparative analysis of the design and test data, this paper concludes that EnergyPlus will optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. At the same time, the multiobjective optimization method and process of the passive energy-saving technology of the near-zero energy consumption building proposed in this paper, as well as the technology combination template under different needs, provide a reference for the selection of the technology path.

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40

Ostrovskii, G. M., and Yu M. Volin. "Multicriteria Optimization of Chemical Processes under Uncertainty." Doklady Chemistry 400, no. 1-3 (January 2005): 12–15. http://dx.doi.org/10.1007/pl00021841.

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41

Sineglazov, Victor M., Kirill D. Riazanovskiy, and Olena I. Chumachenko. "Multicriteria conditional optimization based on genetic algorithms." System research and information technologies, no. 3 (December 7, 2020): 89–104. http://dx.doi.org/10.20535/srit.2308-8893.2020.3.07.

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42

Geng, Shuang, Xiaofu He, Yixin Wang, Hong Wang, Ben Niu, and Kris M. Law. "Multicriteria recommendation based on bacterial foraging optimization." International Journal of Intelligent Systems 37, no. 2 (October 6, 2021): 1618–45. http://dx.doi.org/10.1002/int.22688.

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43

Stott, J., P. Rodgers, Juan Carlos Martínez-Ovando, and S. G. Walker. "Automatic Metro Map Layout Using Multicriteria Optimization." IEEE Transactions on Visualization and Computer Graphics 17, no. 1 (January 2011): 101–14. http://dx.doi.org/10.1109/tvcg.2010.24.

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44

Ng, Kevin Y. K. "A Multicriteria Optimization Approach to Aircraft Loading." Operations Research 40, no. 6 (December 1992): 1200–1205. http://dx.doi.org/10.1287/opre.40.6.1200.

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45

Mehlawat, Mukesh. "Behavioral optimization models for multicriteria portfolio selection." Yugoslav Journal of Operations Research 23, no. 2 (2013): 279–97. http://dx.doi.org/10.2298/yjor130304028m.

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46

Schlaefer, Alexander, Tiberiu Viulet, Alexander Muacevic, and Christoph Fürweger. "Multicriteria optimization of the spatial dose distribution." Medical Physics 40, no. 12 (November 18, 2013): 121720. http://dx.doi.org/10.1118/1.4828840.

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47

Bonnin, Marie, Catherine Azzaro-Pantel, Serge Domenech, and Jacques Villeneuve. "Multicriteria optimization of copper scrap management strategy." Resources, Conservation and Recycling 99 (June 2015): 48–62. http://dx.doi.org/10.1016/j.resconrec.2015.03.013.

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48

Krause, F. L., and F. Golm. "Planning and Multicriteria Optimization of Design Processes." CIRP Annals 45, no. 1 (1996): 145–48. http://dx.doi.org/10.1016/s0007-8506(07)63034-0.

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49

Zhang, W. H. "Pareto optimum sensitivity analysis in multicriteria optimization." Finite Elements in Analysis and Design 39, no. 5-6 (March 2003): 505–20. http://dx.doi.org/10.1016/s0168-874x(02)00106-3.

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50

Fonteix, Christian, Silvère Massebeuf, Fernand Pla, and Laszlo Nandor Kiss. "Multicriteria optimization of an emulsion polymerization process." European Journal of Operational Research 153, no. 2 (March 2004): 350–59. http://dx.doi.org/10.1016/s0377-2217(03)00157-7.

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