Solving high-dimensional global optimization problems using an improved sine cosine algorithm
作者：
Highlights：
• Sine cosine algorithm is modified to solve high-dimensional optimization problem.
• A modified position-updating equation is presented to accelerate convergence.
• A novel nonlinear decreasing conversion parameter strategy is designed to balance exploration and exploitation.
• The performance of ISCA is tested on 24 high-dimensional functions and three engineering design problem.
• Comparisons demonstrate that ISCA is a competitive solver for high-dimensional optimization problems.
摘要
•Sine cosine algorithm is modified to solve high-dimensional optimization problem.•A modified position-updating equation is presented to accelerate convergence.•A novel nonlinear decreasing conversion parameter strategy is designed to balance exploration and exploitation.•The performance of ISCA is tested on 24 high-dimensional functions and three engineering design problem.•Comparisons demonstrate that ISCA is a competitive solver for high-dimensional optimization problems.
论文关键词：Sine cosine algorithm,High-dimensional global optimization,Inertia weight,Engineering design optimization
论文评审过程：Received 29 May 2018, Revised 26 October 2018, Accepted 24 November 2018, Available online 1 December 2018, Version of Record 18 January 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.11.032
