Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem

Abstract

Artificial fish swarm algorithm (AFSA) is one of the critical swarm intelligent algorithms. In this paper, the authors decide to enhance AFSA via diversity operators (AFSA-DO). The diversity operators will be producing more diverse solutions for AFSA to obtain reasonable resolutions. AFSA-DO has been used to solve flexible job shop scheduling problems (FJSSP). However, the FJSSP is a significant problem in the domain of optimization and operation research. Several research papers dealt with methods of solving this issue, including forms of intelligence of the swarms. In this paper, a set of FJSSP target samples are tested employing the improved algorithm to confirm its effectiveness and evaluate its execution. Finally, this paper concludes that the enhanced algorithm via diversity operators has discrepancies about the initial AFSA, and it also provided both sound quality resolution and intersected rate.