A new history-guided multi-objective evolutionary algorithm based on decomposition for batching scheduling

作者：

Highlights：

• A parallel-batch scheduling problem with three objectives is studied.

• A history-guided evolutionary algorithm based on decomposition is proposed.

• Two novel strategies, local competition and internal replacement, are designed.

• Experimental results exhibit the superiority of the proposed algorithm.

摘要

•A parallel-batch scheduling problem with three objectives is studied.•A history-guided evolutionary algorithm based on decomposition is proposed.•Two novel strategies, local competition and internal replacement, are designed.•Experimental results exhibit the superiority of the proposed algorithm.

论文关键词：Multi-objective evolutionary algorithm,Constrained scheduling problem,Local competition,Historical information,Elitist preservation

论文评审过程：Received 7 May 2019, Revised 12 August 2019, Accepted 2 September 2019, Available online 3 September 2019, Version of Record 20 September 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.112920