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SMS-EMOA: Multiobjective selection based on dominated hypervolume

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Cited by:

  1. Weihua Qian & Hang Xu & Houjin Chen & Lvqing Yang & Yuanguo Lin & Rui Xu & Mulan Yang & Minghong Liao, 2024. "A Synergistic MOEA Algorithm with GANs for Complex Data Analysis," Mathematics, MDPI, vol. 12(2), pages 1-30, January.
  2. Houssem R. E. H. Bouchekara & Yusuf A. Sha’aban & Mohammad S. Shahriar & Makbul A. M. Ramli & Abdullahi A. Mas’ud, 2023. "Wind Farm Layout Optimization/Expansion with Real Wind Turbines Using a Multi-Objective EA Based on an Enhanced Inverted Generational Distance Metric Combined with the Two-Archive Algorithm 2," Sustainability, MDPI, vol. 15(3), pages 1-32, January.
  3. Sergio Cabello, 2023. "Faster distance-based representative skyline and k-center along pareto front in the plane," Journal of Global Optimization, Springer, vol. 86(2), pages 441-466, June.
  4. Oliver Schütze & Adanay Martín & Adriana Lara & Sergio Alvarado & Eduardo Salinas & Carlos Coello, 2016. "The directed search method for multi-objective memetic algorithms," Computational Optimization and Applications, Springer, vol. 63(2), pages 305-332, March.
  5. Ivo Couckuyt & Dirk Deschrijver & Tom Dhaene, 2014. "Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization," Journal of Global Optimization, Springer, vol. 60(3), pages 575-594, November.
  6. Hyoungjin Kim & Meng-Sing Liou, 2013. "New fitness sharing approach for multi-objective genetic algorithms," Journal of Global Optimization, Springer, vol. 55(3), pages 579-595, March.
  7. Xiang Yu & Xueqing Zhang, 2017. "Multiswarm comprehensive learning particle swarm optimization for solving multiobjective optimization problems," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-21, February.
  8. Wagner, Markus & Bringmann, Karl & Friedrich, Tobias & Neumann, Frank, 2015. "Efficient optimization of many objectives by approximation-guided evolution," European Journal of Operational Research, Elsevier, vol. 243(2), pages 465-479.
  9. Ying Xu & Rong Qu & Renfa Li, 2013. "A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems," Annals of Operations Research, Springer, vol. 206(1), pages 527-555, July.
  10. Hang Xu, 2024. "A Dynamic Tasking-Based Evolutionary Algorithm for Bi-Objective Feature Selection," Mathematics, MDPI, vol. 12(10), pages 1-23, May.
  11. Andrea Ponti & Antonio Candelieri & Ilaria Giordani & Francesco Archetti, 2023. "Intrusion Detection in Networks by Wasserstein Enabled Many-Objective Evolutionary Algorithms," Mathematics, MDPI, vol. 11(10), pages 1-14, May.
  12. Guerreiro, Andreia P. & Fonseca, Carlos M., 2020. "An analysis of the Hypervolume Sharpe-Ratio Indicator," European Journal of Operational Research, Elsevier, vol. 283(2), pages 614-629.
  13. Peng Cheng & Chun-Wei Lin & Jeng-Shyang Pan, 2015. "Use HypE to Hide Association Rules by Adding Items," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-19, June.
  14. Tangpattanakul, Panwadee & Jozefowiez, Nicolas & Lopez, Pierre, 2015. "A multi-objective local search heuristic for scheduling Earth observations taken by an agile satellite," European Journal of Operational Research, Elsevier, vol. 245(2), pages 542-554.
  15. Ouyang, Haibin & Chen, Jianhong & Li, Steven & Xiang, Jianhua & Zhan, Zhi-Hui, 2023. "Altruistic population algorithm: A metaheuristic search algorithm for solving multimodal multi-objective optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 296-319.
  16. Miettinen, Kaisa & Molina, Julián & González, Mercedes & Hernández-Díaz, Alfredo & Caballero, Rafael, 2009. "Using box indices in supporting comparison in multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 197(1), pages 17-24, August.
  17. Günter Rudolph & Oliver Schütze & Christian Grimme & Christian Domínguez-Medina & Heike Trautmann, 2016. "Optimal averaged Hausdorff archives for bi-objective problems: theoretical and numerical results," Computational Optimization and Applications, Springer, vol. 64(2), pages 589-618, June.
  18. Jesús Martínez-Frutos & David Herrero-Pérez, 2016. "Kriging-based infill sampling criterion for constraint handling in multi-objective optimization," Journal of Global Optimization, Springer, vol. 64(1), pages 97-115, January.
  19. Mohammed Mahrach & Gara Miranda & Coromoto León & Eduardo Segredo, 2020. "Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem," Mathematics, MDPI, vol. 8(11), pages 1-23, November.
  20. Chengyao Wen & Yin Lou, 2023. "On Finding Bi-objective Pareto-optimal Fraud Prevention Rule Sets for Fintech Applications," Papers 2311.00964, arXiv.org, revised Jun 2024.
  21. Sven Schulz & Udo Buscher & Liji Shen, 2020. "Multi-objective hybrid flow shop scheduling with variable discrete production speed levels and time-of-use energy prices," Journal of Business Economics, Springer, vol. 90(9), pages 1315-1343, November.
  22. Carlos Cobos & Cristian Ordoñez & Jose Torres-Jimenez & Hugo Ordoñez & Martha Mendoza, 2024. "Weight Vector Definition for MOEA/D-Based Algorithms Using Augmented Covering Arrays for Many-Objective Optimization," Mathematics, MDPI, vol. 12(11), pages 1-39, May.
  23. Lourdes Uribe & Johan M Bogoya & Andrés Vargas & Adriana Lara & Günter Rudolph & Oliver Schütze, 2020. "A Set Based Newton Method for the Averaged Hausdorff Distance for Multi-Objective Reference Set Problems," Mathematics, MDPI, vol. 8(10), pages 1-29, October.
  24. Luan, Wenpeng & Tian, Longfei & Zhao, Bochao, 2023. "Leveraging hybrid probabilistic multi-objective evolutionary algorithm for dynamic tariff design," Applied Energy, Elsevier, vol. 342(C).
  25. Oliver Cuate & Oliver Schütze, 2020. "Pareto Explorer for Finding the Knee for Many Objective Optimization Problems," Mathematics, MDPI, vol. 8(10), pages 1-24, September.
  26. Dubois-Lacoste, Jérémie & López-Ibáñez, Manuel & Stützle, Thomas, 2015. "Anytime Pareto local search," European Journal of Operational Research, Elsevier, vol. 243(2), pages 369-385.
  27. Yugong Dang & Hongen Ma & Jun Wang & Zhigang Zhou & Zhidong Xu, 2022. "An Improved Multi-Objective Optimization Decision Method Using NSGA-III for a Bivariate Precision Fertilizer Applicator," Agriculture, MDPI, vol. 12(9), pages 1-23, September.
  28. Juergen Branke & Wen Zhang, 2019. "Identifying efficient solutions via simulation: myopic multi-objective budget allocation for the bi-objective case," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 831-865, September.
  29. J. L. Redondo & J. Fernández & P. M. Ortigosa, 2017. "FEMOEA: a fast and efficient multi-objective evolutionary algorithm," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 85(1), pages 113-135, February.
  30. Wang, Ligang & Lampe, Matthias & Voll, Philip & Yang, Yongping & Bardow, André, 2016. "Multi-objective superstructure-free synthesis and optimization of thermal power plants," Energy, Elsevier, vol. 116(P1), pages 1104-1116.
  31. Yunsong Han & Hong Yu & Cheng Sun, 2017. "Simulation-Based Multiobjective Optimization of Timber-Glass Residential Buildings in Severe Cold Regions," Sustainability, MDPI, vol. 9(12), pages 1-18, December.
  32. Wenyu Wang & Christine A. Shoemaker, 2023. "Reference Vector Assisted Candidate Search with Aggregated Surrogate for Computationally Expensive Many Objective Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 318-334, March.
  33. Braun, Marlon & Shukla, Pradyumn, 2024. "On cone-based decompositions of proper Pareto-optimality in multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 317(2), pages 592-602.
  34. Sanath Kahagalage & Hasan Hüseyin Turan & Fatemeh Jalalvand & Sondoss El Sawah, 2023. "A novel graph-theoretical clustering approach to find a reduced set with extreme solutions of Pareto optimal solutions for multi-objective optimization problems," Journal of Global Optimization, Springer, vol. 86(2), pages 467-494, June.
  35. Laumanns, Marco & Zenklusen, Rico, 2011. "Stochastic convergence of random search methods to fixed size Pareto front approximations," European Journal of Operational Research, Elsevier, vol. 213(2), pages 414-421, September.
  36. Álvaro Rubio-Largo & Miguel Vega-Rodríguez & David González-Álvarez, 2015. "Multiobjective swarm intelligence for the traffic grooming problem," Computational Optimization and Applications, Springer, vol. 60(2), pages 479-511, March.
  37. Taimoor Akhtar & Christine Shoemaker, 2016. "Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection," Journal of Global Optimization, Springer, vol. 64(1), pages 17-32, January.
  38. Aparicio, Juan & Monge, Juan F. & Ramón, Nuria, 2021. "A new measure of technical efficiency in data envelopment analysis based on the maximization of hypervolumes: Benchmarking, properties and computational aspects," European Journal of Operational Research, Elsevier, vol. 293(1), pages 263-275.
  39. Chengxin Wen & Hongbin Ma, 2023. "A Two-Stage Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization," Mathematics, MDPI, vol. 11(20), pages 1-25, October.
  40. Lochtefeld, Darrell F. & Ciarallo, Frank W., 2015. "Multi-objectivization Via Decomposition: An analysis of helper-objectives and complete decomposition," European Journal of Operational Research, Elsevier, vol. 243(2), pages 395-404.
  41. Ligang Wang & Zhiping Yang & Shivom Sharma & Alberto Mian & Tzu-En Lin & George Tsatsaronis & François Maréchal & Yongping Yang, 2018. "A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants," Energies, MDPI, vol. 12(1), pages 1-53, December.
  42. Zhenqiang Zhang & Sile Ma & Xiangyuan Jiang, 2022. "Research on Multi-Objective Multi-Robot Task Allocation by Lin–Kernighan–Helsgaun Guided Evolutionary Algorithms," Mathematics, MDPI, vol. 10(24), pages 1-17, December.
  43. António Gaspar-Cunha & Paulo Costa & Wagner de Campos Galuppo & João Miguel Nóbrega & Fernando Duarte & Lino Costa, 2021. "Multi-Objective Optimization of Plastics Thermoforming," Mathematics, MDPI, vol. 9(15), pages 1-20, July.
  44. Prashant Singh & Ivo Couckuyt & Khairy Elsayed & Dirk Deschrijver & Tom Dhaene, 2017. "Multi-objective Geometry Optimization of a Gas Cyclone Using Triple-Fidelity Co-Kriging Surrogate Models," Journal of Optimization Theory and Applications, Springer, vol. 175(1), pages 172-193, October.
  45. Wu Lin & Qiuzhen Lin & Zexuan Zhu & Jianqiang Li & Jianyong Chen & Zhong Ming, 2019. "Evolutionary Search with Multiple Utopian Reference Points in Decomposition-Based Multiobjective Optimization," Complexity, Hindawi, vol. 2019, pages 1-22, April.
  46. Joshua Q. Hale & Helin Zhu & Enlu Zhou, 2020. "Domination Measure: A New Metric for Solving Multiobjective Optimization," INFORMS Journal on Computing, INFORMS, vol. 32(3), pages 565-581, July.
  47. Allmendinger, Richard & Handl, Julia & Knowles, Joshua, 2015. "Multiobjective optimization: When objectives exhibit non-uniform latencies," European Journal of Operational Research, Elsevier, vol. 243(2), pages 497-513.
  48. Gong, Wenyin & Cai, Zhihua, 2009. "An improved multiobjective differential evolution based on Pareto-adaptive [epsilon]-dominance and orthogonal design," European Journal of Operational Research, Elsevier, vol. 198(2), pages 576-601, October.
  49. David Quintana & Roman Denysiuk & Sandra García-Rodríguez & Antonio Gaspar-Cunha, 2017. "Portfolio implementation risk management using evolutionary multiobjective optimization," Post-Print hal-01881379, HAL.
  50. Etay Hay & Sean Hill & Felix Schürmann & Henry Markram & Idan Segev, 2011. "Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of Dendritic and Perisomatic Active Properties," PLOS Computational Biology, Public Library of Science, vol. 7(7), pages 1-18, July.
  51. Liagkouras, Konstantinos & Metaxiotis, Konstantinos, 2021. "Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1019-1036.
  52. Zhang, XuWei & Liu, Hao & Tu, LiangPing & Zhao, Jian, 2020. "An efficient multi-objective optimization algorithm based on level swarm optimizer," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 177(C), pages 588-602.
  53. Audet, Charles & Bigeon, Jean & Cartier, Dominique & Le Digabel, Sébastien & Salomon, Ludovic, 2021. "Performance indicators in multiobjective optimization," European Journal of Operational Research, Elsevier, vol. 292(2), pages 397-422.
  54. Raimundo, Marcos M. & Ferreira, Paulo A.V. & Von Zuben, Fernando J., 2020. "An extension of the non-inferior set estimation algorithm for many objectives," European Journal of Operational Research, Elsevier, vol. 284(1), pages 53-66.
  55. Derbel, Bilel & Humeau, Jérémie & Liefooghe, Arnaud & Verel, Sébastien, 2014. "Distributed localized bi-objective search," European Journal of Operational Research, Elsevier, vol. 239(3), pages 731-743.
  56. Rahat, Alma A.M. & Wang, Chunlin & Everson, Richard M. & Fieldsend, Jonathan E., 2018. "Data-driven multi-objective optimisation of coal-fired boiler combustion systems," Applied Energy, Elsevier, vol. 229(C), pages 446-458.
  57. Liefooghe, Arnaud & Jourdan, Laetitia & Talbi, El-Ghazali, 2011. "A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO," European Journal of Operational Research, Elsevier, vol. 209(2), pages 104-112, March.
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