Constrained evolutionary optimization based on reinforcement learning using the objective function and constraints

作者：

Highlights：

• Q-learning assisted DE is proposed for COPs.

• Hierarchical population is set as state to find the optimal solution.

• Correlation between constraints and objective function is utilized.

• Experimental results demonstrate the efficacy of the algorithm.

摘要

•Q-learning assisted DE is proposed for COPs.•Hierarchical population is set as state to find the optimal solution.•Correlation between constraints and objective function is utilized.•Experimental results demonstrate the efficacy of the algorithm.

论文关键词：Constrained optimization,Reinforcement learning,Adaptive operator selection,Differential evolution

论文评审过程：Received 17 July 2021, Revised 7 November 2021, Accepted 9 November 2021, Available online 23 November 2021, Version of Record 10 January 2022.

论文官网地址：https://doi.org/10.1016/j.knosys.2021.107731