A review on swarm intelligence and evolutionary algorithms for solving flexible job shop scheduling problems

• Main Authors: GAO, Kaizhou, CAO, Zhiguang, ZHANG, Le, CHEN, Zhenghua, HAN, Yuyan, PAN, Quanke
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Evolutionary algorithm; flexible job shop scheduling; review; swarm intelligence; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/8156; https://ink.library.smu.edu.sg/context/sis_research/article/9159/viewcontent/2019IEEECASJAS060403.pdf
• Institution: Singapore Management University

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...