A hybrid pareto-based tabu search for multi-objective flexible job shop scheduling problem with e/t penalty

  • Authors:

  • Junqing Li;Quanke Pan;Shengxian Xie;Jing Liang

  • Affiliations:

  • School of Computer, Liaocheng University, Liaocheng;School of Computer, Liaocheng University, Liaocheng;School of Computer, Liaocheng University, Liaocheng;School of Electrical Engineering, Zhengzhou University, Zhengzhou

  • Venue:
  • ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
  • Year:
  • 2010

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Abstract

In this paper, we propose a Pareto-based tabu search algorithm for multi-objective FJSP with Earliness/Tardiness (E/T) penalty In the hybrid algorithm, several neighboring structure based approaches were proposed to improve the convergence capability of the algorithm while keep population diversity of the last Pareto archive set In addition, an external Pareto archive was developed to record the non-dominated solutions found so far In the hybrid algorithm, dynamic parameters were introduced to adapt to the searching process Experimental on several well-known benchmark instances show that the proposed algorithm is superior to several existing approaches in both solution quality and convergence ability.