A Hybrid Genetic Algorithm for Multi-Objective Multi-Manned Assembly Line Worker Allocation and Balancing Problem

Industrial progress has increased the need to improve the productivity of production systems. In this context, optimizing the problem of allocating and balancing workers on a multi-manned assembly line (MALW-a-BP) is a major challenge. This paper introduces a mathematical model for this issue, as well as a hybrid genetic algorithm (h-GA) dedicated to its solution, with a particular focus on multi-objective optimization, which includes minimizing the cycle time and the total squared workload. Experimental results show that the proposed method outperforms the classical version of the GA, thus confirming the robustness and efficiency of the h-GA.