Modelling and optimization of mixed-parallel straight and two-sided disassembly line balancing problem

Abstract

The recycling of end-of-life (EoL) products is an urgent challenge at present. Disassembly line layout plays a crucial role among the factors that affect recycling efficiency. Subsequently, this study proposed a mixed-parallel straight and two-sided disassembly line layout, combining the advantages of the three layouts to enhance the efficiency of recycling EoL products. Additionally, a mixed-integer non-linear programming (MINLP) model was developed to minimize the number of workstations, idle time balancing, demand, and hazard indices. To solve the mixed-parallel straight and two-sided disassembly line balancing problem (k-MPSTDLBP), this study designed a two-layer non-dominated sorting genetic algorithm-II (NSGA-Ⅱ) with universal encoding and decoding mechanisms. The algorithm’s effectiveness was validated by solving two hybrid cases using both the MINLP model and the two-layer NSGA-II. Moreover, comparative analyses with the non-dominated sorting genetic algorithm-III, the improved artificial fish swarm algorithm, and the improved firefly algorithm demonstrated the superiority of the two-layer NSGA-II. Finally, the two-layer NSGA-II was applied to a hybrid case study involving four types of EoL products under both the mixed-parallel straight and two-sided disassembly line and straight disassembly line layouts, confirming the higher recycling efficiency of the k-MPSTDLBP. Meanwhile, the sensitivity of the two-layer NSGA-II on the k-MPSTDLBP was analyzed using orthogonal experiments.