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Relevant bibliographies by topics / Multiobjective Combinatorial Optimization

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Academic literature on the topic 'Multiobjective Combinatorial Optimization'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 May 2024

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Journal articles on the topic "Multiobjective Combinatorial Optimization"

1

Agrafiotis, D. K. "Multiobjective optimization of combinatorial libraries." IBM Journal of Research and Development 45, no. 3.4 (2001): 545–66. http://dx.doi.org/10.1147/rd.453.0545.

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Köksalan, Murat. "Multiobjective combinatorial optimization: some approaches." Journal of Multi-Criteria Decision Analysis 15, no. 3-4 (2008): 69–78. http://dx.doi.org/10.1002/mcda.425.

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Ehrgott, Matthias. "Multiobjective Optimization." AI Magazine 29, no. 4 (2008): 47. http://dx.doi.org/10.1609/aimag.v29i4.2198.

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Using some real world examples I illustrate the important role of multiobjective optimization in decision making and its interface with preference handling. I explain what optimization in the presence of multiple objectives means and discuss some of the most common methods of solving multiobjective optimization problems using transformations to single objective optimisation problems. Finally, I address linear and combinatorial optimization problems with multiple objectives and summarize techniques for solving them. Throughout the article, I refer to the real world examples introduced at the be

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Barán, Benjamín, and Marcos Villagra. "A Quantum Adiabatic Algorithm for Multiobjective Combinatorial Optimization." Axioms 8, no. 1 (2019): 32. http://dx.doi.org/10.3390/axioms8010032.

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In this work we show how to use a quantum adiabatic algorithm to solve multiobjective optimization problems. For the first time, we demonstrate a theorem proving that the quantum adiabatic algorithm can find Pareto-optimal solutions in finite-time, provided some restrictions to the problem are met. A numerical example illustrates an application of the theorem to a well-known problem in multiobjective optimization. This result opens the door to solve multiobjective optimization problems using current technology based on quantum annealing.

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Ehrgott, Matthias, and Xavier Gandibleux. "Approximative solution methods for multiobjective combinatorial optimization." Top 12, no. 1 (2004): 1–63. http://dx.doi.org/10.1007/bf02578918.

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Bökler, Fritz, Matthias Ehrgott, Christopher Morris, and Petra Mutzel. "Output-sensitive complexity of multiobjective combinatorial optimization." Journal of Multi-Criteria Decision Analysis 24, no. 1-2 (2017): 25–36. http://dx.doi.org/10.1002/mcda.1603.

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Cai, Xinye, Mi Hu, Dunwei Gong, et al. "A decomposition-based coevolutionary multiobjective local search for combinatorial multiobjective optimization." Swarm and Evolutionary Computation 49 (September 2019): 178–93. http://dx.doi.org/10.1016/j.swevo.2019.05.007.

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Pulkkinen, Otto I., Prson Gautam, Ville Mustonen, and Tero Aittokallio. "Multiobjective optimization identifies cancer-selective combination therapies." PLOS Computational Biology 16, no. 12 (2020): e1008538. http://dx.doi.org/10.1371/journal.pcbi.1008538.

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Combinatorial therapies are required to treat patients with advanced cancers that have become resistant to monotherapies through rewiring of redundant pathways. Due to a massive number of potential drug combinations, there is a need for systematic approaches to identify safe and effective combinations for each patient, using cost-effective methods. Here, we developed an exact multiobjective optimization method for identifying pairwise or higher-order combinations that show maximal cancer-selectivity. The prioritization of patient-specific combinations is based on Pareto-optimization in the sea

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SAKAWA, Masatoshi, Masahiro INUIGUCHI, Hideaki SUNADA, and Kazuya SAWADA. "Fuzzy Multiobjective Combinatorial Optimization through Revised Genetic Algorithms." Journal of Japan Society for Fuzzy Theory and Systems 6, no. 1 (1994): 177–86. http://dx.doi.org/10.3156/jfuzzy.6.1_177.

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Domínguez-Ríos, Miguel Ángel, Francisco Chicano, and Enrique Alba. "Effective anytime algorithm for multiobjective combinatorial optimization problems." Information Sciences 565 (July 2021): 210–28. http://dx.doi.org/10.1016/j.ins.2021.02.074.

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Dissertations / Theses on the topic "Multiobjective Combinatorial Optimization"

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Ozpeynirci, Nail Ozgur. "Approaches For Multiobjective Combinatorial Optimization Problems." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609216/index.pdf.

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In this thesis, we consider multiobjective combinatorial optimization problems. We address two main topics. We first address the polynomially solvable cases of the Traveling Salesperson Problem and the Bottleneck Traveling Salesperson Problem. We consider multiobjective versions of these problems with different combinations of objective functions, analyze their computational complexities and develop exact algorithms where possible. We next consider generating extreme supported nondominated points of multiobjective integer programming problems for any number of objective functions. We develop

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Akin, Banu. "Approaches For Special Multiobjective Combinatorial Optimization Problems With Side Constraints." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614603/index.pdf.

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We propose a generic algorithm based on branch-and-bound to generate all efficient solutions of multiobjective combinatorial optimization (MOCO) problems. We present an algorithm specific to multiobjective 0-1 Knapsack Problem based on the generic algorithm. We test the performance of our algorithm on randomly generated sample problems against IBM ILOG CPLEX and we obtain better performance using a problem specific algorithm. We develop a heuristic algorithm by incorporating memory limitations at the expense of solution quality to overcome memory issues of the exact algorithm.

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Paquete, Luís F. "Stochastic local search algorithms for multiobjective combinatorial optimization methods and analysis." Berlin Aka, 2005. http://deposit.ddb.de/cgi-bin/dokserv?id=2770886&prov=M&dok_var=1&dok_ext=htm.

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Schäfer, Luca Elias [Verfasser]. "On Universal and Multiobjective Model Extensions for Combinatorial Optimization Problems / Luca Elias Schäfer." München : Verlag Dr. Hut, 2021. http://d-nb.info/1238422934/34.

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Maach, Fouad. "Bi-objective multi-assignment capacitated location-allocation problem." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/31558.

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Optimization problems of location-assignment correspond to a wide range of real situations, such as factory network design. However most of the previous works seek in most cases at minimizing a cost function. Traffic incidents routinely impact the performance and the safety of the supply. These incidents can not be totally avoided and must be regarded. A way to consider these incidents is to design a network on which multiple assignments are performed. <p> Precisely, the problem we focus on deals with power supplying that has become a more and more complex and crucial question. Many internatio

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Bökler, Fritz [Verfasser], Petra [Akademischer Betreuer] Mutzel, and Matthias [Gutachter] Ehrgott. "Output-sensitive complexity of multiobjective combinatorial optimization with an application to the multiobjective shortest path problem / Friedrich Konstantin Bökler ; Gutachter: Matthias Ehrgott ; Betreuer: Petra Mutzel." Dortmund : Universitätsbibliothek Dortmund, 2018. http://d-nb.info/1168009588/34.

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Rousis, Damon. "A pareto frontier intersection-based approach for efficient multiobjective optimization of competing concept alternatives." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41136.

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The expected growth of civil aviation over the next twenty years places significant emphasis on revolutionary technology development aimed at mitigating the environmental impact of commercial aircraft. As the number of technology alternatives grows along with model complexity, current methods for Pareto finding and multiobjective optimization quickly become computationally infeasible. Coupled with the large uncertainty in the early stages of design, optimal designs are sought while avoiding the computational burden of excessive function calls when a single design change or technology assumptio

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Assis, Laura Silva de 1983. "Otimização de alocação de chaves em redes de distribuição de energia elétrica." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260684.

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Orientadores: Christiano Lyra Filho, Celso Cavellucci<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-25T04:13:51Z (GMT). No. of bitstreams: 1 Assis_LauraSilvade_D.pdf: 3122445 bytes, checksum: 01644f90a086983b8729f81804874faa (MD5) Previous issue date: 2014<br>Resumo: Grande parte das falhas em sistemas elétricos de potência ocorrem por consequência de falhas permanentes nas redes de distribuição. Agências reguladoras definem índices de confiabilidade para quantificar e avaliar a qualidade da di

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Karademir, Serdar. "A Genetic Algorithm For The Biobjective Traveling Salesman Problem With Profits." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/3/12609729/index.pdf.

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In Traveling Salesman Problem (TSP) with profits, a profit is associated with each city and the requirement to visit all cities is removed. The purpose is to simultaneously minimize cost (excluding as many cities as possible) and maximize profit (including as many cities as possible). Although the reduced single-objective case of the problem has been well-studied, the true biobjective problem has been studied only by a few researchers. In this paper we study the true biobjective problem using the Multiobjective Genetic Algorithm NSGA II and the Lin-Kernighan Heuristic. We propose several impro

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Maziere, Florian. "Modèles de parallélisme pour les métaheuristiques multi-objectifs." Thesis, Reims, 2019. http://www.theses.fr/2019REIMS002/document.

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L’objectif de ce projet de trois ans est de proposer des avancées conceptuelles et technologiques dans la résolution de problèmes d’ordonnancement du personnel. L’atteinte de cet objectif passe par la proposition de nouveaux algorithmes basés sur les métaheuristiques et leur implémentation sur les architectures de calcul haute performance. Ce projet s’inscrit en complémentarité du projet HORUS qui bénéficie d’une subvention ANR et qui réunit les expertises scientifiques de deux laboratoires universitaires spécialisés en optimisation et en calcul parallèle : l’équipe SysCom du laboratoire CReST

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Books on the topic "Multiobjective Combinatorial Optimization"

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Gen, Mitsuo. Network models and optimization: Multiobjective genetic algorithm approach. Springer, 2008.

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Paquete, Luis F. Stochastic Local Search Algorithms for Multiobjective Combinatorial Optimizations: Methods and Analysis. IOS Press, 2006.

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Book chapters on the topic "Multiobjective Combinatorial Optimization"

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Kubalik, Jiri, Richard Mordinyi, and Stefan Biffl. "Multiobjective Prototype Optimization with Evolved Improvement Steps." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78604-7_19.

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Upadhayay, Ashutosh, Debdas Ghosh, Jauny, and Nand Kishor. "Cone Method for Uncertain Multiobjective Optimization Problems with Minmax Robustness." In Combinatorial Optimization Under Uncertainty. CRC Press, 2023. http://dx.doi.org/10.1201/9781003329039-8.

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Teghem, Jacques. "Methodologies for Solving Multiobjective Combinatorial Optimization Problems." In Aiding Decisions with Multiple Criteria. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0843-4_22.

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Gutjahr, Walter J. "Two Metaheuristics for Multiobjective Stochastic Combinatorial Optimization." In Stochastic Algorithms: Foundations and Applications. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11571155_12.

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Ehrgott, Matthias, and Xavier Gandibleux. "Multiobjective Combinatorial Optimization — Theory, Methodology, and Applications." In Multiple Criteria Optimization: State of the Art Annotated Bibliographic Surveys. Springer US, 2003. http://dx.doi.org/10.1007/0-306-48107-3_8.

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Li, Hui, Qingfu Zhang, Edward Tsang, and John A. Ford. "Hybrid Estimation of Distribution Algorithm for Multiobjective Knapsack Problem." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24652-7_15.

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Herbawi, Wesam, and Michael Weber. "Evolutionary Multiobjective Route Planning in Dynamic Multi-hop Ridesharing." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20364-0_8.

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Verel, Sébastien, Arnaud Liefooghe, Laetitia Jourdan, and Clarisse Dhaenens. "Pareto Local Optima of Multiobjective NK-Landscapes with Correlated Objectives." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20364-0_20.

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Reichelt, Dirk, and Lars Mönch. "Multiobjective Scheduling of Jobs with Incompatible Families on Parallel Batch Machines." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11730095_18.

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Michalak, Krzysztof. "The Sim-EA Algorithm with Operator Autoadaptation for the Multiobjective Firefighter Problem." In Evolutionary Computation in Combinatorial Optimization. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16468-7_16.

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Conference papers on the topic "Multiobjective Combinatorial Optimization"

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Kumar, Rajeev. "Evolutionary multiobjective combinatorial optimization." In the 2007 GECCO conference companion. ACM Press, 2007. http://dx.doi.org/10.1145/1274000.1274117.

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Kumar, Rajeev. "Evolutionary multiobjective combinatorial optimization (EMCO)." In the 11th annual conference companion. ACM Press, 2009. http://dx.doi.org/10.1145/1570256.1570425.

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Kumar, Rajeev. "Evolutionary multiobjective combinatorial optimization (EMCO)." In the 2008 GECCO conference companion. ACM Press, 2008. http://dx.doi.org/10.1145/1388969.1389079.

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Ishibuchi, Hisao. "Memetic algorithms for evolutionary multiobjective combinatorial optimization." In Industrial Engineering (CIE-40). IEEE, 2010. http://dx.doi.org/10.1109/iccie.2010.5668411.

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Basseur, Matthieu, Adrien Goëffon, Arnaud Liefooghe, and Sébastien Verel. "On set-based local search for multiobjective combinatorial optimization." In Proceeding of the fifteenth annual conference. ACM Press, 2013. http://dx.doi.org/10.1145/2463372.2463430.

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Koliechkina, Liudmyla, Oksana Pichugina, and Olena Dvirna. "Horizontal Method Application to Multiobjective Combinatorial Optimization over Permutations." In 2022 IEEE 3rd International Conference on System Analysis & Intelligent Computing (SAIC). IEEE, 2022. http://dx.doi.org/10.1109/saic57818.2022.9923018.

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Cuevas, Andres, Victor H. Diaz-Ramirez, Vitaly Kober, and Leonardo Trujillo. "Facial recognition using composite correlation filters designed with multiobjective combinatorial optimization." In SPIE Optical Engineering + Applications, edited by Andrew G. Tescher. SPIE, 2014. http://dx.doi.org/10.1117/12.2062348.

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Ye, Te, Zizhen Zhang, Jinbiao Chen, and Jiahai Wang. "Weight-Specific-Decoder Attention Model to Solve Multiobjective Combinatorial Optimization Problems." In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2022. http://dx.doi.org/10.1109/smc53654.2022.9945568.

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Ferreira, Fernando G. D. C., Gustavo P. Hanaoka, Felipe D. Paiva, and Rodrigo T. N. Cardoso. "Parallel MOEAs for Combinatorial Multiobjective Optimization Model of Financial Portfolio Selection." In 2018 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2018. http://dx.doi.org/10.1109/cec.2018.8477688.

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Barroso, Bruno C., Fernando G. D. C. Ferreira, Gustavo P. Hanaoka, Felipe D. Paiva, and Rodrigo T. N. Cardoso. "Composition of investment portfolios through a combinatorial multiobjective optimization model using CVaR." In 2017 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2017. http://dx.doi.org/10.1109/cec.2017.7969519.

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