MOPSO

MOPSO: a proposal for multiple objective particle swarm optimization. This paper introduces a proposal to extend the heuristic called ”particle swarm optimization” (PSO) to deal with multiobjective optimization problems. Our approach uses the concept of Pareto dominance to determine the flight direction of a particle and it maintains previously found nondominated vectors in a global repository that is later used by other particles to guide their own flight. The approach is validated using several standard test functions from the specialized literature. Our results indicate that our approach is highly competitive with current evolutionary multiobjective optimization techniques.


References in zbMATH (referenced in 59 articles )

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  1. Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.: Hierarchical winner-take-all particle swarm optimization social network for neural model fitting (2017)
  2. Halassi, Abdoul-hafar: An attractor-based multiobjective particle swarm optimization (2017)
  3. Jia, Chunhua; Zhu, Hong: An improved multiobjective particle swarm optimization based on culture algorithms (2017)
  4. Jie, Haoxiang; Wu, Yizhong; Zhao, Jianjun; Ding, Jianwan; Liangliang: An efficient multi-objective PSO algorithm assisted by Kriging metamodel for expensive black-box problems (2017)
  5. Liu, Ruochen; Li, Jianxia; Fan, Jing; Mu, Caihong; Jiao, Licheng: A coevolutionary technique based on multi-swarm particle swarm optimization for dynamic multi-objective optimization (2017)
  6. Tian, Mingzheng; Hou, Kuolin; Wang, Zhaowei; Wan, Zhongping: An improved cuckoo search algorithm for multi-objective optimization (2017)
  7. Behravan, Iman; Dehghantanha, Oveis; Zahiri, Seyed Hamid; Mehrshad, Nasser: An optimal SVM with feature selection using multiobjective PSO (2016)
  8. Devika, K.; Jafarian, A.; Hassanzadeh, A.; Khodaverdi, R.: Optimizing of bullwhip effect and net stock amplification in three-echelon supply chains using evolutionary multi-objective metaheuristics (2016)
  9. Smairi, Nadia; Siarry, Patrick; Ghedira, Khaled: A hybrid particle swarm approach based on tribes and tabu search for multi-objective optimization (2016)
  10. Feng, Ting-Cheng; Li, Tzuu-Hseng S.; Kuo, Ping-Huan: Variable coded hierarchical fuzzy classification model using DNA coding and evolutionary programming (2015)
  11. Girsang, Abba Suganda; Tsai, Chun-Wei; Yang, Chu-Sing: Repairing the inconsistent fuzzy preference matrix using multiobjective PSO (2015)
  12. Govindan, Kannan; Jafarian, Ahmad; Nourbakhsh, Vahid: Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic (2015)
  13. Li, Jianping; Sun, Xiaolei; Wang, Fei; Wu, Dengsheng: Risk integration and optimization of oil-importing maritime system: a multi-objective programming approach (2015)
  14. Moritz, Ruby L. V.; Reich, Enrico; Schwarz, Maik; Bernt, Matthias; Middendorf, Martin: Refined ranking relations for selection of solutions in multi objective metaheuristics (2015)
  15. Poonthalir, Ganesan; Nadarajan, Rethnaswamy; Geetha, Shanmugam: Vehicle routing problem with limited refueling halts using particle swarm optimization with greedy mutation operator (2015)
  16. Yang, Guang; Xu, Tao; Li, Xiang; Xiu, Haohua; Xu, Tianshuang: An efficient hybrid algorithm for multiobjective optimization problems with upper and lower bounds in engineering (2015)
  17. Attea, Bara’a A.; Khalil, Enan A.; Özdemir, Suat: Biologically inspired probabilistic coverage for mobile sensor networks (2014) ioport
  18. Deb, Kalyanmoy; Padhye, Nikhil: Enhancing performance of particle swarm optimization through an algorithmic link with genetic algorithms (2014)
  19. Kotinis, Miltiadis: Improving a multi-objective differential evolution optimizer using fuzzy adaptation and (K)-medoids clustering (2014) ioport
  20. Qasem, Sultan Noman; Shamsuddin, Siti Mariyam; Hashim, Siti Zaiton Mohd; Darus, Maslina; Al-Shammari, Eiman: Memetic multiobjective particle swarm optimization-based radial basis function network for classification problems (2013) ioport