A multi-objective cellular genetic algorithm for energy-oriented balancing and sequencing problem of mixed-model assembly line

Abstract

Energy shortage has led to increasing concerns regarding energy-efficient manufacturing systems. In this study, an energy-oriented balancing and sequencing problem of mixed-model assembly line is proposed along with a cellular strategy-based genetic Algorithm. First, a bi-objective mathematical model with energy consumption and balance rate is developed. Second, a multi-objective algorithm that integrates a cellular strategy and local search is presented to solve this bi-objective problem. Third, a set of benchmark problems is generated; the parameters of the algorithm are carefully set using the Taguchi method. The performance of the proposed algorithm is shown from two aspects: by a comparison with the algorithm without the cellular strategy and by a comparison with a non-dominated sorting genetic algorithm. Both the comparisons are conducted based on three given criteria.