Fast Evolutionary Solution Finding for Optimization Using Opposite Gradient Movement

摘要：

In this paper, a hybrid algorithm of gradient movement is proposed. On a surface of continuous function, every random point has a gradient value of the function that minimize and convergence to zero when it is a neighborhood with the optimum solution. Each iteration calculates the gradient of function at every point and chooses a minimum gradient point with a shortest distance from the optimum solution to find a new closer candidate to be an optimum point. The comparative experiments were made between CA_PSO, PSO, CACO, and SGA. Results show the proposed algorithm with gradient movement techniques outperforms other.

关键词： Swarm intelligence Ant colony optimization (ACO) Particle swarm optimization (PSO) Gradient Continuous Function Optimization

作者: Thirachit Saenphon Chidchanok Lursinsap

作者单位: Advanced Virtual and Intelligent (AVIC) Center Department of Mathematics, Faculty of Science Chulalongkorn University, Bangkok, Thailand

会议类型: 国际会议

会议名称: 2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

会议地点: 上海

会议语种:英文

页码: 1524-1527

在线出版日期: 2011-07-26（万方平台首次上网日期，不代表论文的发表时间）