reviewIEEE/CAA Journal of Automatica SinicaJun 19, 2019GREEN OA

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

Indexed incrossref

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

535
total citations
FWCI
57.22
Percentile
100%
References
175
Citations per year

Authors

6

Topics & keywords

Keywords
  • Job shop scheduling
  • Initialization
  • Computer science
  • Mathematical optimization
  • Population
  • Evolutionary algorithm
  • Swarm intelligence
  • Algorithm
UN Sustainable Development Goals
  • Decent work and economic growth
No related works found for this paper.