A multi-population, multi-objective memetic algorithm for energy-efficient job-shop scheduling with deteriorating machines

作者：

Highlights：

• Energy-efficient job-shop scheduling with deteriorating machines is studied.

• Green production and tardiness related objectives are considered.

• A multi-population, multi-objective memetic algorithm is proposed for the problem.

• The proposed algorithm exhibits superior performance across a range of metrics.

摘要

•Energy-efficient job-shop scheduling with deteriorating machines is studied.•Green production and tardiness related objectives are considered.•A multi-population, multi-objective memetic algorithm is proposed for the problem.•The proposed algorithm exhibits superior performance across a range of metrics.

论文关键词：Job-shop scheduling,Machine speed scaling,Cumulative deterioration effect,Maintenance activity,Memetic algorithm,Periodic local search

论文评审过程：Received 15 December 2019, Revised 15 February 2020, Accepted 27 February 2020, Available online 28 February 2020, Version of Record 14 May 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113348