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

Authors

Alaa Wagih Abdulqader, Computer Techniques Engineering Department, Baghdad College of Economic Sciences University, Baghdad, IraqFollow
Sura Mazin Ali, Political Sciences College, Mustansiriyah University, Baghdad, IraqFollow

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.

Keywords

Combinatorial Optimization Problems, Diversity Operators, Fish Swarm Artificial Algorithm, Flexible Job Shop Scheduling problem, Metaheuristic Algorithm

Article Type

Supplemental Issue

How to Cite this Article

Abdulqader, Alaa Wagih and Ali, Sura Mazin (2023) "Diversity Operators-based Artificial Fish Swarm Algorithm to Solve Flexible Job Shop Scheduling Problem," Baghdad Science Journal: Vol. 20: Iss. 5, Article 29.
DOI: https://doi.org/10.21123/bsj.2023.6810