A fitness-based weighting mechanism for multicriteria flowshop scheduling using genetic algorithms

摘要

The most effective approximate methods to tackle the problem of scheduling jobs in a permutation flowshop with the bicriteria of makespan and maximum tardiness are based on genetic algorithms (GA). In these methods, the performance of the GA is improved by applying local search to all offsprings belonging to the current population. To do so, the two objectives must be aggregated into a single objective, which is usually accomplished by weighting them into a scalar function. Since the weighting scheme is considered to be critical for the performance of the algorithm, several weighting mechanisms have been suggested in the literature. In this paper, we propose two new weighting schemes and conduct an extensive computational experience under a variety of parameter settings in order to show their effectiveness as compared to existing ones.