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Journal articles on the topic 'Multicriterial optimization'

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Published: 30 May 2022

Last updated: 31 May 2022

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1

Podinovski, V. V. "Potential optimality in multicriterial optimization." Computational Mathematics and Mathematical Physics 54, no. 3 (March 2014): 429–38. http://dx.doi.org/10.1134/s0965542514030154.

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2

Zypkin, Ya Z., and A. S. Krasnenker. "Man Machine Methods for Multicriterial Optimization." IFAC Proceedings Volumes 21, no. 19 (June 1988): 271–72. http://dx.doi.org/10.1016/s1474-6670(17)54504-8.

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3

Vuleta, Jovo. "Visekriterijumska optimizacija izbora izvodjaca projekta." Ekonomski anali 44, no. 157 (2003): 7–40. http://dx.doi.org/10.2298/eka0357007v.

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The selection of the best (multicriterial optimal) contractors for project realization is analised in this paper. This problem is one of the most important problems that occurs during the realization of every project, especially the complex one. First we point the problem importance and past experiences and results in its solving. As a conclusion, we state that the problem of selection project realization contractors has been solved by discovering any possible solution, not necessary the optimal one. We have tried to solve one real problem using the model of integer multicriterial optimization type 0-1. The problem was presented by the appropriate mathematical model whose solving leads to multicriterial optimal solution. The special attention was paid to technique and procedure for solving the given model of integer multicriterial optimization. In order to minimize the efforts, the model has been transformed in corresponding network model whose further solving is based on the theory of graphs. The presented procedure decreases the number of mathematical operations and is more simply than most of the usual methods for solving the integer multicriterial type 0-1 optimization problems. At the end, the recommended procedure has been illustrated by a numerical example.

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4

Bogó-Tóth, Zs, and Z. Lakner. "Multicriterial optimization of liquid food packaging systems." Acta Alimentaria 43, Supplement 1 (November 2014): 29–35. http://dx.doi.org/10.1556/aalim.43.2014.suppl.5.

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5

Vladimirova, L. V. "Multicriterial approach to beam dynamics optimization problem." Journal of Physics: Conference Series 747 (September 2016): 012070. http://dx.doi.org/10.1088/1742-6596/747/1/012070.

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6

Gawlicki, Michał, and Łukasz Jankowski. "Trajectory Identification for Moving Loads by Multicriterial Optimization." Sensors 21, no. 1 (January 5, 2021): 304. http://dx.doi.org/10.3390/s21010304.

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Moving load is a fundamental loading pattern for many civil engineering structures and machines. This paper proposes and experimentally verifies an approach for indirect identification of 2D trajectories of moving loads. In line with the “structure as a sensor” paradigm, the identification is performed indirectly, based on the measured mechanical response of the structure. However, trivial solutions that directly fit the mechanical response tend to be erratic due to measurement and modeling errors. To achieve physically meaningful results, these solutions need to be numerically regularized with respect to expected geometric characteristics of trajectories. This paper proposes a respective multicriterial optimization framework based on two groups of criteria of a very different nature: mechanical (to fit the measured response of the structure) and geometric (to account for the geometric regularity of typical trajectories). The state-of-the-art multiobjective genetic algorithm NSGA-II is used to find the Pareto front. The proposed approach is verified experimentally using a lab setup consisting of a plate instrumented with strain gauges and a line-follower robot. Three trajectories are tested, and in each case the determined Pareto front is found to properly balance between the mechanical response fit and the geometric regularity of the trajectory.

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7

Staib, Tilo. "Necessary Optimality Conditions for Nonsmooth Multicriterial Optimization Problems." SIAM Journal on Optimization 2, no. 1 (February 1992): 153–71. http://dx.doi.org/10.1137/0802009.

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8

Kokhanovskii, V. A., and D. V. Glazunov. "Multicriterial Optimization of the Composition of a Lubricant." Journal of Machinery Manufacture and Reliability 49, no. 7 (December 2020): 624–32. http://dx.doi.org/10.3103/s1052618820070080.

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9

Koleva, E., L. Koleva, Dm Trushnikov, G. Kolev, and Z. Petrova. "Multicriterial optimization strategies for electron beam welding processes." Journal of Physics: Conference Series 2240, no. 1 (March 1, 2022): 012038. http://dx.doi.org/10.1088/1742-6596/2240/1/012038.

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Abstract The electron beam welding process is analyzed of high-strength steel type 15Cr5Mo samples with deflection oscillations along the zone of interaction. The geometries of the molten and the heat affected zones are studied in order to investigate the influence of the deflection oscillations parameters and to improve the seam quality. A robust engineering approach is implemented for the case of production conditions considering the errors in the process parameter settings. The problem of quality improvement through fulfilling pre-set technological and quality requirements is solved by scalarization of the vector criteria by implementing a reference point strategy. Other multicriterial optimization strategies are also proposed.

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10

Bucur, Amelia. "Aspects Of Multicriterial Mathematical Modeling And Of The Fuzzy Formalism For The Hierarchization Of Study Programs Based On Several Quality Characteristics." ACTA Universitatis Cibiniensis 67, no. 1 (September 1, 2015): 1–6. http://dx.doi.org/10.1515/aucts-2015-0055.

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Abstract The aim of this paper is to present aspects of mathematical modeling for the hierarchization of study programs from universities, based on several quality characteristics. The tools used pertain to multicriterial optimization, to the different methods of assessing importance coefficients, to the utility theory, the fuzzy formalism, and to the fuzzy simple additive weighting method. The conclusion is that multicriterial decision-making methods can be efficiently used in assessing the quality of study programs, noting that, just like other methods from the decision theory, the multicriterial decision-making methods highlight aspects of problems differently, therefore, there can be no comparison or competitiveness between them, and choosing one over the other is up to the decision-maker.

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11

Melo Brentan, Bruno, Gustavo Meirelles Lima, Antonio Carlos Zuffo, and Edevar Luvizotto Junior. "Dimensionamento de redes de distribuição de água por meio de análise multicriterial." Revista DAE 221, no. 68 (2019): 118–30. http://dx.doi.org/10.36659/dae.2020.010.

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O dimensionamento de redes de distribuição de água (RDAs) é feito para que as restrições operacionais de velo- cidade e pressão se mantenham dentro de limites que garantam a eficiência operacional. Assim, buscam-se as tubulações de menor custo para que essas condições sejam satisfeitas. Entretanto, ao adotar essa prática, ou- tras características da rede podem ser afetadas negativamente, como sua resiliência e capacidade de expansão. Dessa forma, este trabalho apresenta um estudo de caso em que a análise multicriterial é utilizada para realizar o dimensionamento de uma RDA. Primeiramente, um mapa cognitivo é feito para identificar os principais cri- térios a serem considerados na solução do problema. Em seguida, o método Delphi é usado em conjunto com o Analytic Hierarchy Process (AHP) para determinar os pesos relativos de cada critério. Por fim, três diferentes métodos de análise multicritérios são utilizados para a solução do problema: AHP, Electre e Promethee. Palavras-chave: Rede de distribuição. Otimização. Análise multicritério. Abstract The design of water distribution networks (WDNs) is made to match velocity and pressure constraints that guaran- tee operational efficiency. Thus, pipes with lower cost are selected to attend these conditions. However, this proce- dure can harm other characteristics of the network, as for example its resilience and expansion capacity. Therefore, this paper presents a case study in which the multicriterial analysis is used to design a WDN. First, a cognitive map is built to identify the main criteria to be considered during the design process. Then, the Delphi method is used jointly with the Analytic Hierarchy Process (AHP) to define the relative weights of each criteria. Finally, three different methods for multicriterial analysis are used to solve the problem: AHP, Electre and Promethee. Keywords: Water distribution network. Optimization. Multicriterial analysis.

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12

Mormul', N. F., and Yu M. Pochtman. "Multicriterial optimization of stiffened composite panels under combined loading." Mechanics of Composite Materials 29, no. 6 (1994): 606–12. http://dx.doi.org/10.1007/bf00616327.

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13

Smetanin, S. D., and V. G. Shalamov. "Multicriterial Optimization of Rotary Milling in Producing Elementary Chip." Russian Engineering Research 41, no. 11 (November 2021): 1087–90. http://dx.doi.org/10.3103/s1068798x21110253.

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14

Zaslavsky, Aleksey. "Modification of the label method for problems of multicriterial optimization." Economics and the Mathematical Methods 56, no. 1 (2020): 95. http://dx.doi.org/10.31857/s042473880008559-3.

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15

Palchykov, Oleg O. "MULTICRITERIAL OPTIMIZATION OF TRANSFORMERS WITH A ROTATING MAG-NETIC FIELD." ELECTRICAL AND COMPUTER SYSTEMS 22, no. 98 (May 25, 2016): 122–28. http://dx.doi.org/10.15276/eltecs.22.98.2016.21.

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16

Котелевська ., Ю. В., С. В. Гадецька, and О. В. Глушко. "LOAN PORTFOLIO OPTIMIZATION BY HIERARCHICAL MODEL OF MULTICRITERIAL DECISION MAKING." Financial and credit activity: problems of theory and practice 1, no. 16 (October 22, 2014): 184. http://dx.doi.org/10.18371/fcaptp.v1i16.28520.

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17

Vladimirova, Ludmila V. "On Application of Multicriterial Optimization in Partical Beam Control Problem." IFAC Proceedings Volumes 33, no. 16 (July 2000): 385–89. http://dx.doi.org/10.1016/s1474-6670(17)39662-3.

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18

Kovalenko, Anna, and Gennady Rogachev. "Multicriterial optimization of preventive maintenance of informational/technical stochastic system." ITM Web of Conferences 6 (2016): 01002. http://dx.doi.org/10.1051/itmconf/20160601002.

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19

Kostreva, M. M., Quan Zheng, and Deming Zhuang. "A method for approximating solutions Of multicriterial nonlinear Optimization problems." Optimization Methods and Software 5, no. 3 (January 1995): 209–26. http://dx.doi.org/10.1080/10556789508805611.

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20

Gergel, Victor, and Evgeny Kozinov. "Efficient multicriterial optimization based on intensive reuse of search information." Journal of Global Optimization 71, no. 1 (February 19, 2018): 73–90. http://dx.doi.org/10.1007/s10898-018-0624-3.

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21

Staib, T. "On necessary and sufficient optimality conditions for multicriterial optimization problems." ZOR Zeitschrift f�r Operations Research Methods and Models of Operations Research 35, no. 3 (May 1991): 231–48. http://dx.doi.org/10.1007/bf01415909.

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22

Rozin, S. G., I. E. Rubin, and I. M. Soboĺ. "On multicriterial optimization in reactor problems using Monte Carlo calculations." Progress in Nuclear Energy 24, no. 1-3 (January 1990): 231–36. http://dx.doi.org/10.1016/0149-1970(90)90040-c.

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23

Muzalewska, Małgorzata. "Methodology of Multicriterial Optimization of Geometric Features of an Orthopedic Implant." Applied Sciences 11, no. 22 (November 22, 2021): 11070. http://dx.doi.org/10.3390/app112211070.

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The main purpose of the article is to describe the methodology used for multi-criteria optimization of the geometric features of the orthopedic implant used for the reconstruction of the anterior cruciate ligament located in the knee joint. The methodology includes: 1. Method of development of the bones of the knee joint model; 2. Method of multi-criteria optimization of the geometric features of the orthopedic implant using an artificial immune system, the objective function and the Pareto front; 3. Expert evaluation method based on forms. The work confirmed that the assumed thesis, a multi-criteria optimization using an artificial immune system, which is a specially defined objective function, and the Pareto method, which allows to determine the geometrical features of the implant, will lead to fulfill optimal blood perfusion and sufficient strength properties of the implant simultaneously. We conclude that the described methodology allowed to achieve the optimal geometrical features of the orthopedic implant used for reconstruction of the anterior cruciate ligament located in the knee joint.

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24

Altherr, Lena C., Thorsten Ederer, Philipp Pöttgen, Ulf Lorenz, and Peter F. Pelz. "Multicriterial Optimization of Technical Systems Considering Multiple Load and Availability Scenarios." Applied Mechanics and Materials 807 (November 2015): 247–56. http://dx.doi.org/10.4028/www.scientific.net/amm.807.247.

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Cheap does not imply cost-effective -- this is rule number one of zeitgeisty system design. The initial investment accounts only for a small portion of the lifecycle costs of a technical system. In fluid systems, about ninety percent of the total costs are caused by other factors like power consumption and maintenance. With modern optimization methods, it is already possible to plan an optimal technical system considering multiple objectives. In this paper, we focus on an often neglected contribution to the lifecycle costs: downtime costs due to spontaneous failures. Consequently, availability becomes an issue.

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25

Valeriu, DRAGAN. "Aerodynamic reconfiguration and multicriterial optimization of centrifugal compressors – a case study." INCAS BULLETIN 6, no. 4 (December 5, 2014): 41–49. http://dx.doi.org/10.13111/2066-8201.2014.6.4.4.

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26

Muzalewska, Małgorzata, and Wojciech Moczulski. "Methodology of multicriterial optimization of the design of an orthopedic implant." Mechanik, no. 2 (February 2016): 122–24. http://dx.doi.org/10.17814/mechanik.2016.2.15.

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27

Logunova, O. S., E. G. Filippov, I. V. Pavlov, and V. V. Pavlov. "Multicriterial optimization of the batch composition for steel-smelting arc furnaces." Steel in Translation 43, no. 1 (January 2013): 34–38. http://dx.doi.org/10.3103/s0967091213010051.

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28

Koleva, E., L. Koleva, V. Vassileva, K. Vutova, and Ts Tsonevska. "Model-based multicriterial optimization of electron beam melting and refining of copper." Journal of Physics: Conference Series 2240, no. 1 (March 1, 2022): 012037. http://dx.doi.org/10.1088/1742-6596/2240/1/012037.

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Abstract Experimental results on the quality of electron beam melting and refining of copper samples by implementing the “method of washers” are analyzed by using an empirical model estimation approach. The influence is studied of the process parameters – melting power and time of refining, on the residual content of impurities, the refining rate, the overall removal efficiency and the material losses. A graphical user interface is designed and developed for calculation, investigation and multicriterial optimization of the quality of the refined copper samples.

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29

Gergel, V. P., and E. A. Kozinov. "Accelerating Parallel Multicriterial Optimization Methods Based on Intensive Using of Search Information." Procedia Computer Science 108 (2017): 1463–72. http://dx.doi.org/10.1016/j.procs.2017.05.051.

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30

Dolgui, A. B., A. V. Eremeev, and V. S. Sigaev. "Analysis of a multicriterial buffer capacity optimization problem for a production line." Automation and Remote Control 78, no. 7 (July 2017): 1276–89. http://dx.doi.org/10.1134/s0005117917070098.

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31

RABIEJ, MAŁGORZATA. "Application of multicriterial optimization for determination of crystallinity degree of semicrystalline polymers." Polimery 48, no. 04 (April 2003): 288–95. http://dx.doi.org/10.14314/polimery.2003.288.

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32

Ventura, Tiago, Humberto Rocha, Brigida da Costa Ferreira, Joana Dias, and Maria do Carmo Lopes. "Comparison of two beam angular optimization algorithms guided by automated multicriterial IMRT." Physica Medica 64 (August 2019): 210–21. http://dx.doi.org/10.1016/j.ejmp.2019.07.012.

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33

Andrianov, A. A., I. S. Kuptsov, and T. V. Utyanskaya. "Some Results of Multicriterial and Robust Optimization of Nuclear Power Systems Structure." Atomic Energy 123, no. 1 (November 2017): 10–16. http://dx.doi.org/10.1007/s10512-017-0293-1.

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34

Pochtman, Yu M., L. V. Derevyanko, and N. F. Mormul'. "Multicriterial optimization of hybrid composite cylindrical shells under a stochastic combined loading." Mechanics of Composite Materials 26, no. 6 (1991): 801–6. http://dx.doi.org/10.1007/bf00656667.

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35

Meler-Kapcia, Maria. "Algorithm for searching out similar ships within expert system of computer aided preliminary design of ship power plant." Polish Maritime Research 15, no. 3 (October 1, 2008): 92–96. http://dx.doi.org/10.2478/v10012-007-0089-7.

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Algorithm for searching out similar ships within expert system of computer aided preliminary design of ship power plant This paper presents an algorithm for searching out similar ships, implemented in a hybrid system for aiding preliminary design of ship power plant, based on new similarity functions as well as those adapted from literature sources. For searching out similar ships a multicriterial optimization method of weighed profits was applied.

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36

Toktoshov, Gulzhigit Y., Anastasiya N. Yurgenson, and Denis A. Migov. "COMPLEXITY ANALYSIS OF OPTIMIZATION PROBLEMS OF UTILITYCOMMUNICATIONS NETWORKS." T-Comm 14, no. 9 (2020): 17–23. http://dx.doi.org/10.36724/2072-8735-2020-14-9-17-23.

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The problems of optimizing engineering communications networks according to various criteria, such as, minimum total construction costs, reliability, and compatibility are considered. A new technique for modeling utility networks based on the hypernet model, which allows one to take into account the nesting of one structure in another and the interdependence of indicators of the elements of these structures, is proposed. This approach makes the considered in these paper optimizations problems universal, and allows to take into account the interaction of the designed types of networks with each other. In addition, by combining the problems presented in this paper, various variations of optimization problems can be obtained. In this case, multicriterial tasks are stated, such as design networks of minimum cost, taking into account their reliability; design networks of minimum cost, taking into account their compatibility and reliability, and others. Note that all these problems are NP-hard, for the solution of which do not exist polynomial exacts algorithms. In particular, it was shown that the optimization problem in the simplest hypernet formulation is NP-hard. The possibility of applying accurate and approximate methods for solving them, and assessing the accuracy of these methods, were examined.

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37

Rabiej, Małgorzata. "A hybrid immune–evolutionary strategy algorithm for the analysis of the wide-angle X-ray diffraction curves of semicrystalline polymers." Journal of Applied Crystallography 47, no. 5 (August 16, 2014): 1502–11. http://dx.doi.org/10.1107/s1600576714014782.

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Decomposition of wide-angle X-ray diffraction curves into crystalline peaks and amorphous components is one of the most difficult nonlinear optimization problems. For this reason, the elaboration of a reliable method that provides fast unambiguous solutions remains an important and topical task. This work presents a hybrid system dedicated to this aim, combining two methods of artificial intelligence – evolution strategies and an immune algorithm – with the classical method of Rosenbrock. A combination of the mechanisms of these three methods has given a very effective and convergent algorithm that performs very well a multicriterial optimization. Tests have shown that it is faster to converge and less ambiguous than the genetic algorithm.

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38

Myronenko, Yevhenii, Serhii Mirantsov, Vitalii Guzenko, and Denys Guzenko. "SOFTWARE AND MATHEMATICAL COMPLEX FOR MULTICRITERIAL OPTIMIZATION OF TURNING PARAMETERS ON HEAVY MACHINES." Cutting & Tools in Technological System, no. 92 (July 1, 2020): 53–61. http://dx.doi.org/10.20998/2078-7405.2020.92.07.

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39

Bobkov, V. I., V. V. Borisov, M. I. Dli, and V. P. Meshalkin. "Multicriterial optimization of the energy efficiency of the thermal preparation of raw materials." Theoretical Foundations of Chemical Engineering 49, no. 6 (November 2015): 842–46. http://dx.doi.org/10.1134/s0040579515060020.

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40

Wilfert, H. H., J. Fischer, Ch Hoy, and J. Uhlig. "Multicriterial Load Flow Optimization and Conirol Action's Selection in High Voltage Grid Systems." IFAC Proceedings Volumes 28, no. 26 (December 1995): 335–40. http://dx.doi.org/10.1016/s1474-6670(17)44780-x.

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41

Ancău, Mircea, and Cristian Caizar. "The computation of Pareto-optimal set in multicriterial optimization of rapid prototyping processes." Computers & Industrial Engineering 58, no. 4 (May 2010): 696–708. http://dx.doi.org/10.1016/j.cie.2010.01.015.

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42

Zhadan, V. G. "A method for the parametric representation of objective functions in conditional multicriterial optimization." USSR Computational Mathematics and Mathematical Physics 26, no. 1 (January 1986): 108–15. http://dx.doi.org/10.1016/0041-5553(86)90193-x.

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43

Naumov, Anatoly Aleksandrovich. "TO S_P-INSTABILITY OF NORMALIZATION OF MULTICRITERIAL CRITERIA METHOD FOR DECIDING OF OPTIMIZATION PROBLEMS." Theoretical & Applied Science 5, no. 09 (September 30, 2013): 14–17. http://dx.doi.org/10.15863/tas.2013.09.5.2.

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44

Lebedeva, Т. Т., N. V. Semenova, and T. I. Sergienko. "Stability kernel of vector optimization problems under perturbations of criterion functions." Reports of the National Academy of Sciences of Ukraine, no. 1 (February 2021): 17–23. http://dx.doi.org/10.15407/dopovidi2021.01.017.

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The article is devoted to the study of the influence of uncertainty in initial data on the solutions of optimiza-tion multicriterial problems. In the optimization problems, including problems with vector criterion, small per-turbations in initial data can result in solutions strongly different from the true ones. The results of the con-ducted researches allow us to extend the known class of vector optimization problems, stable with respect to in-put data perturbations in vector criterion. We are talking about stability in the sense of Hausdorff lower semicontinuity for point-set mapping that characterizes the dependence of the set of optimal solutions on the input data of the vector optimization problem. The conditions of stability against input data perturbations in vector criterion for the problem of finding Pareto optimal solutions with continuous partial criterion func-tions and feasible set of arbitrary structure are obtained by studying the sets of points that are stable belonging and stable not belonging to the Pareto set.

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45

Marrazzo, Livia, Chiara Arilli, Roberto Pellegrini, Pierluigi Bonomo, Silvia Calusi, Cinzia Talamonti, Marta Casati, Antonella Compagnucci, Lorenzo Livi, and Stefania Pallotta. "Automated planning through robust templates and multicriterial optimization for lung VMAT SBRT of lung lesions." Journal of Applied Clinical Medical Physics 21, no. 6 (April 10, 2020): 114–20. http://dx.doi.org/10.1002/acm2.12872.

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46

Khonkiv, М., S. Teterina, S. Danylenko, and O. Potemska. "Use of multicriterial optimization of the growth medium for accumulation of biomass of lactic acid bacteria." Scientific Works of National University of Food Technologies 26, no. 4 (August 2020): 47–57. http://dx.doi.org/10.24263/2225-2924-2020-26-4-7.

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47

Lagerev, I. A. "DESIGN OF TURNING HYDRAULIC ENGINES FOR MANIPULATORS OF MOBILE MACHINES ON THE BASIS OF MULTICRITERIAL OPTIMIZATION." Nauchno-tekhnicheskiy vestnik Bryanskogo gosudarstvennogo universiteta 2, no. 4 (December 25, 2016): 34–51. http://dx.doi.org/10.22281/2413-9920-2016-02-04-34-51.

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48

Breedveld, Sebastiaan, Pascal R. M. Storchi, Peter W. J. Voet, and Ben J. M. Heijmen. "iCycle: Integrated, multicriterial beam angle, and profile optimization for generation of coplanar and noncoplanar IMRT plans." Medical Physics 39, no. 2 (January 31, 2012): 951–63. http://dx.doi.org/10.1118/1.3676689.

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49

Morariu, D.-I., D. Lepădatu, and I. Șerbănoiu. "Multicriterial optimization of topo-geodetic techniques for behaviour monitoring in service stage of civil engineering structures." IOP Conference Series: Materials Science and Engineering 789 (June 6, 2020): 012041. http://dx.doi.org/10.1088/1757-899x/789/1/012041.

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50

Arakelyan, E. K., S. A. Minasyan, and G. E. Agababyan. "Methodical principles of multicriterial optimization of daily operating conditions of power equipment at thermal power stations." Thermal Engineering 53, no. 10 (October 2006): 767–71. http://dx.doi.org/10.1134/s0040601506100028.

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