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

Authors: Xiaohong Zhang; Zhe Zhang; Xiaoling Song; Xiaofang Zhong

Addresses: School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094, China ' School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094, China

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]

Keywords: seru production system; setup times; scheduling; genetic algorithm; branch-and-bound.

DOI: 10.1504/EJIE.2025.144703

European Journal of Industrial Engineering, 2025 Vol.19 No.2, pp.190 - 236

Received: 31 Oct 2022
Accepted: 25 Sep 2023

Published online: 28 Feb 2025 *

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