A Non-Dominated Sorting Particle Swarm Optimization Algorithm For Mixed-Model Assembly Line Sequencing Problem

Abstract

Mixed-model assembly line (MMAL) sequencing is a typical problem that various models of a common base product are assembled on the same line. In this paper, we proposed products assembly sequencing in mixed-model assembly lines as a multiple-objective optimization problem with the objectives to minimize material consumption waviness, the total setup cost, and total task overlapped time. These three objectives are typically inversely correlated with each other, and simultaneously optimization of the three objectives is challenging. The multi-objective optimization algorithm based on non-dominated sorting particle swarm optimization (NSPSO) is designed. We conduct an extensive experiment study in which the performance of the proposed NSPSO is compared against non-dominated genetic algorithm (NSGA II). The computational results show that the proposed NSPSO outperforms NSGA II, significantly in large-sized problems.