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Evolving better population distribution and exploration in evolutionary multi-objective optimization

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  • Tan, K.C.
  • Goh, C.K.
  • Yang, Y.J.
  • Lee, T.H.

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  • Tan, K.C. & Goh, C.K. & Yang, Y.J. & Lee, T.H., 2006. "Evolving better population distribution and exploration in evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 171(2), pages 463-495, June.
  • Handle: RePEc:eee:ejores:v:171:y:2006:i:2:p:463-495
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    References listed on IDEAS

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    1. Sarker, Ruhul & Liang, Ko-Hsin & Newton, Charles, 2002. "A new multiobjective evolutionary algorithm," European Journal of Operational Research, Elsevier, vol. 140(1), pages 12-23, July.
    2. Jones, D. F. & Mirrazavi, S. K. & Tamiz, M., 2002. "Multi-objective meta-heuristics: An overview of the current state-of-the-art," European Journal of Operational Research, Elsevier, vol. 137(1), pages 1-9, February.
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    Citations

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    Cited by:

    1. Zhang, Rui & Chang, Pei-Chann & Wu, Cheng, 2013. "A hybrid genetic algorithm for the job shop scheduling problem with practical considerations for manufacturing costs: Investigations motivated by vehicle production," International Journal of Production Economics, Elsevier, vol. 145(1), pages 38-52.
    2. Tan, K.C. & Chiam, S.C. & Mamun, A.A. & Goh, C.K., 2009. "Balancing exploration and exploitation with adaptive variation for evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 197(2), pages 701-713, September.
    3. Tzu-Li Chen & Chen-Yang Cheng & Yi-Han Chou, 2020. "Multi-objective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming," Annals of Operations Research, Springer, vol. 290(1), pages 813-836, July.
    4. Ding, Jian-Ya & Song, Shiji & Wu, Cheng, 2016. "Carbon-efficient scheduling of flow shops by multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 248(3), pages 758-771.
    5. 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.
    6. Chen, Jianyong & Lin, Qiuzhen & Ji, Zhen, 2010. "A hybrid immune multiobjective optimization algorithm," European Journal of Operational Research, Elsevier, vol. 204(2), pages 294-302, July.
    7. Rui Zhang, 2017. "Environment-Aware Production Scheduling for Paint Shops in Automobile Manufacturing: A Multi-Objective Optimization Approach," IJERPH, MDPI, vol. 15(1), pages 1-32, December.
    8. Rui Zhang, 2017. "Sustainable Scheduling of Cloth Production Processes by Multi-Objective Genetic Algorithm with Tabu-Enhanced Local Search," Sustainability, MDPI, vol. 9(10), pages 1-26, September.
    9. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS," European Journal of Operational Research, Elsevier, vol. 218(3), pages 735-746.
    10. Mansouri, S. Afshin & Aktas, Emel & Besikci, Umut, 2016. "Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption," European Journal of Operational Research, Elsevier, vol. 248(3), pages 772-788.

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