Industrial Engineering and Management Systems

  • 제10권3호
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  • Pages.203-208
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  • 2011
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  • 1598-7248(pISSN)
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  • 2234-6473(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
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Differential Evolution Algorithm for Job Shop Scheduling Problem

  • Wisittipanich, Warisa (Industrial and Manufacturing Engineering School of Engineering and Technology, Asian Institute of Technology) ;
  • Kachitvichyanukul, Voratas (Industrial and Manufacturing Engineering School of Engineering and Technology, Asian Institute of Technology)
  • 투고 : 2011.02.22
  • 심사 : 2011.08.06
  • 발행 : 2011.09.01
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초록

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

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참고문헌

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  5. Integrating scheduling with optimal sublot for parallel machine with job splitting and dependent setup times vol.137, pp.None, 2011, https://doi.org/10.1016/j.cie.2019.106095
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