JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (5): 21-28.doi: 10.6040/j.issn.1672-3961.1.2016.215

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Multi-objective scheduling in no-wait flow shop using a hybridized differential evolution algorithm

DENG Guanlong1, YANG Hongyong1, ZHANG Shuning1, GU Xingsheng2   

  1. 1. School of Information and Electrical Engineering, Ludong University, Yantai 264025, Shandong, China;
    2. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
  • Received:2016-03-01 Online:2016-10-20 Published:2016-03-01

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Abstract: To sovle the no-wait flow shop scheduling with the makespan and total flow time criteria, a multi-objective differential evolution algorithm hybridized with variable neighborhood search(MDEVNS)was proposed. A diversified population initialization method was proposed by using the improved Nawaz-Enscore-Ham(NEH)heuristics. The updating operations of mutant, trial and target individuals were developed in differential evolution. To improve the multi-objective searching ability, a multi-objective variable neighborhood search was embedded in the algorithm. The computational experiments based on Taillard benchmark set revealed that the MDEVNS yielded Pareto front solutions with better diversity and performance than the multi-objective simulated annealing algorithm and the non-dominated sorting genetic algorithm, and the effectiveness of the MDEVNS for multi-objective scheduling in no-wait flow shop was proved.

Key words: differential evolution, flow shop, intelligent algorithm, multi-objective optimization, production scheduling

CLC Number: 

  • TP273
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