A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows
作者:
Highlights:
• A distributed no-wait flow shop scheduling problem with due windows is proposed.
• A discrete knowledge-guided learning fruit fly optimization is designed.
• The KNEHdw based on no-wait problem property knowledge is introduced.
• A probability knowledge model with learning and feedback is designed.
• The variable neighborhood descent (VND) strategy is employed.
摘要
•A distributed no-wait flow shop scheduling problem with due windows is proposed.•A discrete knowledge-guided learning fruit fly optimization is designed.•The KNEHdw based on no-wait problem property knowledge is introduced.•A probability knowledge model with learning and feedback is designed.•The variable neighborhood descent (VND) strategy is employed.
论文关键词:Distributed no-wait flow-shop,Due windows,Fruit fly optimization,Probability knowledge model,Variable neighborhood descend
论文评审过程:Received 20 October 2021, Revised 11 January 2022, Accepted 14 March 2022, Available online 19 March 2022, Version of Record 25 March 2022.
论文官网地址:https://doi.org/10.1016/j.eswa.2022.116921