Boosted kernel search: Framework, analysis and case studies on the economic emission dispatch problem
作者：
Highlights：
• The kernel parameter’s calculation is simplified to improve KSO algorithm.
• A local search of the hill-climbing algorithm is utilized for KSO’s exploitation.
• IKSO is compared with some classic and popular MAs on benchmark functions.
• The performance of IKSO is evaluated in different dimensions and types.
• IKSO has achieved a much better performance than other literature MAs in EED problem.
摘要
•The kernel parameter’s calculation is simplified to improve KSO algorithm.•A local search of the hill-climbing algorithm is utilized for KSO’s exploitation.•IKSO is compared with some classic and popular MAs on benchmark functions.•The performance of IKSO is evaluated in different dimensions and types.•IKSO has achieved a much better performance than other literature MAs in EED problem.
论文关键词：Global optimization,Meta-heuristic algorithm,Kernel search algorithm,Swarm intelligence,Evolutionary algorithm,Economic emission dispatch problem,Dispatch
论文评审过程：Received 16 January 2021, Revised 31 July 2021, Accepted 21 September 2021, Available online 24 September 2021, Version of Record 4 October 2021.
论文官网地址：https://doi.org/10.1016/j.knosys.2021.107529
