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Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems

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Abstract

This paper presents a hybrid Pareto-based discrete artificial bee colony algorithm for solving the multi-objective flexible job shop scheduling problem. In the hybrid algorithm, each solution corresponds to a food source, which composes of two components, i.e., the routing component and the scheduling component. Each component is filled with discrete values. A crossover operator is developed for the employed bees to learn valuable information from each other. An external Pareto archive set is designed to record the non-dominated solutions found so far. A fast Pareto set update function is introduced in the algorithm. Several local search approaches are designed to balance the exploration and exploitation capability of the algorithm. Experimental results on the well-known benchmark instances and comparisons with other recently published algorithms show the efficiency and effectiveness of the proposed algorithm.

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Authors and Affiliations

  1. College of Computer Science, Liaocheng University, Liaocheng, 252059, People’s Republic of China

    Jun-Qing Li, Quan-Ke Pan & Kai-Zhou Gao

  2. State Key Lab. of Digital Manufacturing Equipment & Technology in Huazhong University of Science & Technology, Wuhan, 430074, People’s Republic of China

    Quan-Ke Pan

Authors
  1. Jun-Qing Li
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  2. Quan-Ke Pan
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  3. Kai-Zhou Gao
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Correspondence to Jun-Qing Li.

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Li, JQ., Pan, QK. & Gao, KZ. Pareto-based discrete artificial bee colony algorithm for multi-objective flexible job shop scheduling problems. Int J Adv Manuf Technol 55, 1159–1169 (2011). https://doi.org/10.1007/s00170-010-3140-2

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  • DOI: https://doi.org/10.1007/s00170-010-3140-2

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