A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems
Macau University of Science and Technology · National University of Singapore · +4 more institutions
Abstract
Flexible job shop scheduling problems (FJSP) have received much attention from academia and industry for many years. Due to their exponential complexity, swarm intelligence (SI) and evolutionary algorithms (EA) are developed, employed and improved for solving them. More than 60% of the publications are related to SI and EA. This paper intents to give a comprehensive literature review of SI and EA for solving FJSP. First, the mathematical model of FJSP is presented and the constraints in applications are summarized. Then, the encoding and decoding strategies for connecting the problem and algorithms are reviewed. The strategies for initializing algorithms? population and local search operators for improving…
Citation impact
- FWCI
- 57.22
- Percentile
- 100%
- References
- 175
Authors
6- KGKaizhou GaoCorresponding
Macau University of Science and Technology
- ZCZhiguang Cao
National University of Singapore
- LZLe Zhang
Institute for Infocomm Research, Agency for Science, Technology and Research
- ZCZhenghua Chen
Agency for Science, Technology and Research, Institute for Infocomm Research
- YHYuyan Han
Liaocheng University
Topics & keywords
- Job shop scheduling
- Initialization
- Computer science
- Mathematical optimization
- Population
- Evolutionary algorithm
- Swarm intelligence
- Algorithm
- Decent work and economic growth