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A hybrid approach of genetic algorithm and truncated branch-and-bound for seru scheduling problem with sequence-dependent setup time

Author

Listed:
  • Xiaohong Zhang
  • Zhe Zhang
  • Xiaoling Song
  • Xiaofang Zhong

Abstract

This paper concentrates on the seru scheduling problem considering sequence-dependent setup time to minimise the makespan, in which seru production system (SPS) is a new-type advanced manufacturing system to respond quickly to volatile market. A mixed-integer programming (MIP) model is formulated, and then a hybridisation of genetic algorithm with a truncated branch-and-bound method (GATBB) is designed to speed up the solving process. Truncated branch-and-bound (TBB) procedure is employed to find a better solution than the initial one given by the GA within a tighter upper bound. Computational experiments are carried out finally, and a series of results of experiments, analyses of variance (ANOVA), and Tukey test show that the GATBB algorithm significantly outperforms the GA and GA-PSO algorithm. Specifically, GATBB algorithm performs extremely well in finding high-quality solutions efficiently, and can find approximate and even exact solutions for instances with up to 100 products. [Received: 31 October 2022; Accepted: 25 September 2023]

Suggested Citation

  • Xiaohong Zhang & Zhe Zhang & Xiaoling Song & Xiaofang Zhong, 2025. "A hybrid approach of genetic algorithm and truncated branch-and-bound for seru scheduling problem with sequence-dependent setup time," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 19(2), pages 190-236.
    • Handle: RePEc:ids:eujine:v:19:y:2025:i:2:p:190-236
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