A new simple, fast and efficient algorithm for global optimization over continuous search-space problems: Radial Movement Optimization
作者：
Highlights：
• We propose a new stochastic global optimization method for continuous search-space.
• We chose ten benchmark functions to evaluate the ability of the proposed algorithm.
• The results are compared with two other methods which are PSO and DE.
• The proposed method obtains proper and fast solution and escapes from local optima.
• Being robust, fast and needing less memory are the main features of the method.
摘要
•We propose a new stochastic global optimization method for continuous search-space.•We chose ten benchmark functions to evaluate the ability of the proposed algorithm.•The results are compared with two other methods which are PSO and DE.•The proposed method obtains proper and fast solution and escapes from local optima.•Being robust, fast and needing less memory are the main features of the method.
论文关键词：Global optimization,Stochastic optimization,Non-linear optimization,Swarm intelligence,Radial Movement Optimization
论文评审过程：Available online 18 October 2014.
论文官网地址：https://doi.org/10.1016/j.amc.2014.09.102
