JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2017, Vol. 47 ›› Issue (4): 25-30.doi: 10.6040/j.issn.1672-3961.0.2016.256

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Improved bi-variables estimation of distribution algorithms for multi-objective permutation flow shop scheduling problem

PEI Xiaobing1, CHEN Huifen1*, ZHANG Baizhan2, CHEN Menghui2   

  1. 1. School of Management, Tianjin University of Technology, Tianjin 300384, China;
    2. School of Software, Nanchang University, Nanchang 330031, Jiangxi, China
  • Received:2016-07-14 Online:2017-08-20 Published:2016-07-14

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Abstract: Aiming at permutation flow shop scheduling problem(PFSP)with the minimum maximum makespan, the minimum maximum tardiness and the minimum total flow time as objectives, improved bi-variable estimation of distribution algorithm(IBVEDA)based on bi-variables estimation of distribution algorithm(BVEDA)was proposed. Building blocks was designed using bi-variable probability model of IBVEDA, according to combination probability formula for block competition and block mining, then artificial chromosomes were generated using high quality blocks to improve the quality of solution in the evolution process. To enhance the diversity of algorithm, dispatching rules, the shortest processing time, longest processing time,earliest due date were added in parallel evolution while injecting artificial chromosomes, the number of individual for next iteration processed by the methods above depended on the above methods top 10 total weighted fitness of last iteration to do dynamic adjustment, finally Pareto dominance was used to select and save non-dominated solutions. The experiment used C++ code tested on Taillards standard instances, IBVEDA was compared with SPGAⅡand BVEDA and solution distribution of the three algorithms were plot which the effectiveness of IBVEDA was validated.

Key words: bi-variables estimation of distribution algorithm, permutation flow shop scheduling, dispatching rules, multi-objective optimation, probability model

CLC Number: 

  • TP301
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