文献类型：期刊文献

英文题名：A Novel Multi-objective Cultural Algorithm Embedding Five-Element Cycle Optimization

作者：Mao, Zhengyan[1]; Xiang, Yue[1]; Zhang, Yijie[1]; Liu, Mandan[1]

机构：[1] East China University of Science and Technology, School of Information Science and Engineering, Shanghai, China

年份：2020

外文期刊名：2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

收录：EI(收录号：20204109317212)

语种：英文

外文关键词：Computation theory - Evolutionary algorithms

摘要：The cultural algorithm, as a dual-inheritance framework designed for optimization problems, can incorporate any population-adopted evolutionary computation technique in its population space. On the other hand, based on the Five-Elements Cycle Model derived from the ancient Chinese Five Elements (metal, wood, water, fire, earth) theory, the five-elements cycle optimization algorithm was proved to be effective in solving continuous function optimization problems. In this work, we propose a multi-objective cultural algorithm with a five-elements-cycle-optimization-based population space, where the five-element cycle model is adopted as the evolution scheme in the population space of the cultural algorithm framework. Simulation results on 12 classic benchmark problems show that the proposed algorithm can effectively solve continuous optimization functions and obtains satisfactory non-dominated solutions compared with 8 representative multi-objective algorithms. ? 2020 IEEE.