Solving Multi-Objective Two-Sided Assembly Line Balancing Problems by Harmony Search Algorithm Based on Pareto Entropy

Abstract

Two-sided assembly lines are designed to produce large and complex products, where workers can perform on both sides at the same time. This paper establishes a mathematical model for the multi-objective two-sided assembly line balancing problems with additional constraints (MOATALBP). The model considers both workers' skill and balance of the assembly line, aimings to maximize efficiency and minimize the workers cost and smoothness index. A harmony search algorithm(HS) based on Pareto entropy (PE-MHS) is proposed to solve MOATALBP. The difference entropy of Pareto solutions is employed to adjust algorithm parameters to enhance optimization ability of PE-MHS. Moreover, the finetuning operation combining insertion and inverse sequence is utilized to avoid the algorithm falling into local optima. Ultimately, non-dominated sorting ensures a set of well-distributed Pareto solutions. The experimental results of different problems indicate that the proposed algorithm can achieve better solutions than three classical algorithms (NSGAII, SPEA2 and HS) for the MOATALBP. INDEX TERMSHarmony search algorithm, multi-objective optimization, pareto entropy, two-sided assembly line balancing.

A new multiobjective tiki-taka algorithm for optimization of assembly line balancing

“…The two-sided line is suitable for assembling large products such as automobile and household appliances. Besides considering the number of workstations, the two-sided ALB also focuses to minimize the mated workstations (Zheng et al ., 2021).…”