Improved sine cosine algorithm with crossover scheme for global optimization
作者：
Highlights：
• A new method called ISCA is proposed for global optimization problems.
• The ISCA improves the SCA using crossover and personal best memory of agents.
• The classical, CEC 2014 and CEC 2017 benchmarks are used to examine ISCA.
• The ISCA is used for engineering problems and image thresholding problem.
• Comparisons illustrate the improvement on the performance of ISCA.
摘要
•A new method called ISCA is proposed for global optimization problems.•The ISCA improves the SCA using crossover and personal best memory of agents.•The classical, CEC 2014 and CEC 2017 benchmarks are used to examine ISCA.•The ISCA is used for engineering problems and image thresholding problem.•Comparisons illustrate the improvement on the performance of ISCA.
论文关键词：Optimization,Population based algorithms,Sine cosine algorithm,Engineering optimization problems,Multilevel thresholding
论文评审过程：Received 2 September 2018, Revised 4 December 2018, Accepted 6 December 2018, Available online 17 December 2018, Version of Record 7 January 2019.
论文官网地址：https://doi.org/10.1016/j.knosys.2018.12.008
