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Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems

Jin-hui Yang1; Liang Sun1; Heow Pueh Lee2,3; Yun Qian4; Yan-chun Liang1   

  1. 1. College of Computer Science and Technology, Jilin University, Key Laboratory of Symbol Computation and
    Knowledge Engineering of Ministry of Education, Changchun 130012, P. R. China
    2. Institute of High Performance Computing, Singapore 117528, Singapore
    3. Department of Mechanical Engineering, National University of Singapore, Singapore 117576, Singapore
    4. Institute of Electric and Information Engineering, Beihua University, Jilin 132021, P. R. China
  • Received:2008-01-12 Revised:2008-05-03 Online:2008-06-30 Published:2008-05-03
  • Contact: Yan-chun Liang

Abstract: A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki’s neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algo-rithm.

Key words: clonal selection algorithm, job shop scheduling problem, simulated annealing, global search, local search