Dynamic optimization in binary search spaces via weighted superposition attraction algorithm
作者：
Highlights：
• Several versions of WSA algorithm for dynamic optimization in binary search spaces.
• A novel method to generate a binary vector from a binary population.
• Several versions of FA and PSO for dynamic optimization in binary search spaces.
• Comparison of several transfer functions including s-shaped and modular methods.
• Hyper-heuristic framework to use low-level heuristics in local search stage.
摘要
•Several versions of WSA algorithm for dynamic optimization in binary search spaces.•A novel method to generate a binary vector from a binary population.•Several versions of FA and PSO for dynamic optimization in binary search spaces.•Comparison of several transfer functions including s-shaped and modular methods.•Hyper-heuristic framework to use low-level heuristics in local search stage.
论文关键词：Dynamic optimization,Weighted superposition attraction algorithm,Firefly algorithm,Binary optimization,Transfer functions
论文评审过程：Received 16 August 2017, Revised 6 November 2017, Accepted 23 November 2017, Available online 2 December 2017, Version of Record 22 December 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.048
