Diversified Particle Swarm Optimization for Hybrid Flowshop Scheduling

Document Type: Original Manuscript

Author

Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran

10.22094/joie.2018.671.1433

Abstract

The aim of this paper is to propose a new particle swarm optimization algorithm to solve a hybrid flowshop scheduling with sequence-dependent setup times problem, which is of great importance in the industrial context. This algorithm is called diversified particle swarm optimization algorithm which is a generalization of particle swarm optimization algorithm and inspired by an anarchic society whose members behave anarchically to improve their situations. Such anarchy lets the algorithm explore the solution space perfectly and prevent falling in the local optimum traps. Besides, for the first time, for the hybrid flowshop, we proposed eight different local search algorithms and incorporate them into the algorithm in order to improve it with the help of systematic changes of the neighborhood structure within a search for minimizing the makespan. The proposed algorithm was tested and the numerical results showe that the proposed algorithm significantly outperforms other effective heuristics recently developed.

Graphical Abstract

Diversified Particle Swarm Optimization for Hybrid Flowshop Scheduling

Highlights

  • This paper introduces diversified particle swarm optimization with local search.
  • DPSO is inspired by a society whose members behave anarchically.
  • In DPSO, the particles fickleness increases as their situations become worse.
  • The performance of the DPSO is examined  on sequence-dependent hybrid flowshop. 

Keywords

Main Subjects


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