Modified multi-objective evolutionary programming algorithm for solving project scheduling problems

作者：

Highlights：

• Scheduling problems were solved using Multi-Objective Evolutionary Programming MOEP.

• Evolutionary Programming (EP) doesn’t use crossover which cause dependency violation.

• EP showed robustness in solving objective functions of highly correlated parameters.

• New mutation operator is employed to accommodate scheduling problems.

• MOEP was benchmarked against SPEA-II and NSGA-II.

摘要

•Scheduling problems were solved using Multi-Objective Evolutionary Programming MOEP.•Evolutionary Programming (EP) doesn’t use crossover which cause dependency violation.•EP showed robustness in solving objective functions of highly correlated parameters.•New mutation operator is employed to accommodate scheduling problems.•MOEP was benchmarked against SPEA-II and NSGA-II.

论文关键词：Multi-objective optimization,Evolutionary programming,Project scheduling

论文评审过程：Received 8 July 2020, Revised 11 April 2021, Accepted 2 June 2021, Available online 11 June 2021, Version of Record 19 June 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115338