A multiple search strategies based grey wolf optimizer for solving multi-objective optimization problems
作者：
Highlights：
• A multi-objective grey wolf optimizer algorithm with multiple search strategies is developed.
• The developed algorithm is evaluated on a series of benchmark functions.
• The performance of the algorithm is compared with well-known algorithms using various metrics.
• A novel constraints handling method used for optimal scheduling problem of cascade hydropower stations is designed.
• The algorithm is firstly applied to optimize multi-objective optimal scheduling problem of cascade hydropower stations.
摘要
•A multi-objective grey wolf optimizer algorithm with multiple search strategies is developed.•The developed algorithm is evaluated on a series of benchmark functions.•The performance of the algorithm is compared with well-known algorithms using various metrics.•A novel constraints handling method used for optimal scheduling problem of cascade hydropower stations is designed.•The algorithm is firstly applied to optimize multi-objective optimal scheduling problem of cascade hydropower stations.
论文关键词：Multi-objective grey wolf optimizer,Multiple search strategies,Multi-objective optimal scheduling problem,Cascade hydropower stations,Constraints handling methods
论文评审过程：Received 13 July 2019, Revised 12 December 2019, Accepted 12 December 2019, Available online 13 December 2019, Version of Record 20 December 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.113134
