Multi-objective evolutionary algorithms with heuristic decoding for hybrid flow shop scheduling problem with worker constraint

作者：

Highlights：

• Hybrid flow shop scheduling model with worker constraint is constructed as MILP.

• Multi-objective evolutionary algorithms with heuristic decoding (MOEAH) are proposed.

• Seven different heuristic decoding methods are designed in MOEAH.

摘要

•Hybrid flow shop scheduling model with worker constraint is constructed as MILP.•Multi-objective evolutionary algorithms with heuristic decoding (MOEAH) are proposed.•Seven different heuristic decoding methods are designed in MOEAH.

论文关键词：Heuristic,Hybrid flow shop,Scheduling,Worker constraint,Evolutionary algorithm

论文评审过程：Received 9 December 2019, Revised 13 October 2020, Accepted 7 November 2020, Available online 11 November 2020, Version of Record 24 January 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114282