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Resource allocation model and double-sphere crowding distance for evolutionary multi-objective optimization

Author

Listed:
  • Lei, Yu
  • Gong, Maoguo
  • Zhang, Jun
  • Li, Wei
  • Jiao, Licheng

Abstract

Convergence speed and diversity of nondominated solutions are two important performance indicators for Multi-Objective Evolutionary Algorithms (MOEAs). In this paper, we propose a Resource Allocation (RA) model based on Game Theory to accelerate the convergence speed of MOEAs, and a novel Double-Sphere Crowding Distance (DSCD) measure to improve the diversity of nondominated solutions. The mechanism of RA model is that the individuals in each group cooperate with each other to get maximum benefits for their group, and then individuals in the same group compete for private interests. The DSCD measure uses hyper-spheres consisting of nearest neighbors to estimate the crowding degree. Experimental results on convergence speed and diversity of nondominated solutions for benchmark problems and a real-world problem show the efficiency of these two proposed techniques.

Suggested Citation

  • Lei, Yu & Gong, Maoguo & Zhang, Jun & Li, Wei & Jiao, Licheng, 2014. "Resource allocation model and double-sphere crowding distance for evolutionary multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 234(1), pages 197-208.
    • Handle: RePEc:eee:ejores:v:234:y:2014:i:1:p:197-208
    DOI: 10.1016/j.ejor.2013.09.007
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    References listed on IDEAS

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    1. Hu, Zhi-Hua, 2010. "A multiobjective immune algorithm based on a multiple-affinity model," European Journal of Operational Research, Elsevier, vol. 202(1), pages 60-72, April.
    2. 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.
    3. Tan, K.C. & Goh, C.K. & Mamun, A.A. & Ei, E.Z., 2008. "An evolutionary artificial immune system for multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 187(2), pages 371-392, June.
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    Cited by:

    1. Jiang, Yuanchun & Liu, Yezheng & Shang, Jennifer & Yildirim, Pinar & Zhang, Qingfu, 2018. "Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives," European Journal of Operational Research, Elsevier, vol. 267(2), pages 612-627.
    2. Yu Lei & Jiao Shi, 2017. "A NNIA Scheme for Timetabling Problems," Journal of Optimization, Hindawi, vol. 2017, pages 1-11, May.

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