An improved Opposition-Based Sine Cosine Algorithm for global optimization
作者：
Highlights：
• A new method to solve global optimization and engineering problems called OBSCA.
• The proposed method improves the SCA by using opposite-based learning.
• We apply the OBSCA over mathematical benchmark functions.
• We test OBSCA in engineering optimization problems.
• Comparisons support the improvement on the performance of OBCSA.
摘要
•A new method to solve global optimization and engineering problems called OBSCA.•The proposed method improves the SCA by using opposite-based learning.•We apply the OBSCA over mathematical benchmark functions.•We test OBSCA in engineering optimization problems.•Comparisons support the improvement on the performance of OBCSA.
论文关键词：Sine Cosine Algorithms (SCA),Opposition-Based Learning (OBL),Metaheuristic (MH),Engineering problems
论文评审过程：Received 5 May 2017, Revised 21 July 2017, Accepted 22 July 2017, Available online 15 August 2017, Version of Record 31 August 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.07.043
