A bi-objective dynamic collaborative task assignment under uncertainty using modified MOEA/D with heuristic initialization
作者：
Highlights：
• A collaborative task assignment model under uncertainty is formulated.
• The population is initialized using a constructive heuristic algorithm.
• Decomposition-based multi-objective optimizer is enhanced with some modifications.
• Taguchi method with a novel response is applied to tune the parameters.
• Statistical results show the good performance of the proposed algorithms.
摘要
•A collaborative task assignment model under uncertainty is formulated.•The population is initialized using a constructive heuristic algorithm.•Decomposition-based multi-objective optimizer is enhanced with some modifications.•Taguchi method with a novel response is applied to tune the parameters.•Statistical results show the good performance of the proposed algorithms.
论文关键词：Task assignment,Uncertainty,MOEA/D,Heuristic,Taguchi method
论文评审过程：Received 22 April 2019, Revised 8 July 2019, Accepted 25 July 2019, Available online 26 July 2019, Version of Record 2 September 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.112844
