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Multi-objective Optimization of the Distributed Permutation Flow Shop Scheduling Problem with Transportation and Eligibility Constraints

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Abstract

In this paper, we consider the distributed permutation flow shop scheduling problem (DPFSSP) with transportation and eligibility constrains. Three objectives are taken into account, i.e., makespan, maximum lateness and total costs (transportation costs and setup costs). To the best of our knowledge, there is no published work on multi-objective optimization of the DPFSSP with transportation and eligibility constraints. First, we present the mathematics model and constructive heuristics for single objective; then, we propose an improved The Nondominated Sorting Genetic Algorithm II (NSGA-II) for the multi-objective DPFSSP to find Pareto optimal solutions, in which a novel solution representation, a new population re-/initialization, effective crossover and mutation operators, as well as local search methods are developed. Based on extensive computational and statistical experiments, the proposed algorithm performs better than the well-known NSGA-II and the Strength Pareto Evolutionary Algorithm 2 (SPEA2).

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Acknowledgements

The authors wish to thank the anonymous referees for their constructive comments. The authors would like to thank Professor Bo Liu for his discussions and constant encouragement.

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Authors and Affiliations

  1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Shuang Cai, Ke Yang & Ke Liu

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Shuang Cai, Ke Yang & Ke Liu

  3. Key Laboratory of Management, Decision and Information Systems, Chinese Academy of Sciences, Beijing, 100190, China

    Ke Liu

  4. National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing, 100190, China

    Ke Liu

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  1. Shuang Cai
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Correspondence to Shuang Cai.

Additional information

This research was partially supported by the National Natural Science Foundation of China (Nos. 71390334 and 11271356).

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Cai, S., Yang, K. & Liu, K. Multi-objective Optimization of the Distributed Permutation Flow Shop Scheduling Problem with Transportation and Eligibility Constraints. J. Oper. Res. Soc. China 6, 391–416 (2018). https://doi.org/10.1007/s40305-017-0165-3

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