Industrial Engineering and Management Systems

Korean Institute of Industrial Engineers (대한산업공학회)
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An Efficient PSO Algorithm for Finding Pareto-Frontier in Multi-Objective Job Shop Scheduling Problems

  • Wisittipanich, Warisa (Industrial Engineering, Faculty of Engineering, Chiang Mai University) ;
  • Kachitvichyanukul, Voratas (Industrial and Manufacturing Engineering, School of Engineering and Technology, Asian Institute of Technology)
  • Received : 2012.08.30
  • Accepted : 2013.05.03
  • Published : 2013.06.30
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Abstract

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.

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References

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