Memory based Hybrid Dragonfly Algorithm for numerical optimization problems
作者：
Highlights：
• A novel hybrid algorithm (MHDA) based on Dragon Fly and PSO is proposed.
• Performance is tested using standard benchmark problems.
• Proposed algorithm is compared with well-known optimization algorithms.
• Statistical analysis is done using Friedman’s test and Wilcoxon signed ranksum test.
• Superiority of MHDA is also proved by applying on engineering design problems.
摘要
•A novel hybrid algorithm (MHDA) based on Dragon Fly and PSO is proposed.•Performance is tested using standard benchmark problems.•Proposed algorithm is compared with well-known optimization algorithms.•Statistical analysis is done using Friedman’s test and Wilcoxon signed ranksum test.•Superiority of MHDA is also proved by applying on engineering design problems.
论文关键词：Dragonfly algorithm,Particle Swarm Optimization,Hybridization,Benchmark functions,Engineering problems,Friedman’s test
论文评审过程：Received 5 January 2017, Revised 27 February 2017, Accepted 17 April 2017, Available online 18 April 2017, Version of Record 24 April 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.04.033
