吸引排斥机制求解全局优化问题

Attraction–repulsion Mechanism for Solving Global Optimization Problem

全局优化问题是现代优化设计方法的研究热点。本文在传统全局优化方法的基础上介绍了电磁场吸引排斥机制并将其应用在求解韦伯问题的优化问题中;然后,有效结合传统的优化方法和随机性优化方法,引出了类电磁机制算法,该算法具有收敛速度快、计算精度高的优点,可以实现整个解空间上的分布式信息搜索等特点;最后,试探性的指出类电磁吸引排斥机制目前存在的问题及其研究发展方向。

Global optimization problem is hotspot of modern optimal design method. Base the tradition on global optimization method, this paper introduces an attraction-repulsion mechanism in the magnetic field which applies optimization problem to solve weber problem. Then, it combines the traditional optimization method with stochastic optimization method to educe an electromagnetism-like mechanism. The algorithm accelerates the convergence speed and improves the precision of the solutions and achieves the distributed information search on the entire solution space. Last,the research and problems of an attraction-repulsion mechanism arc pointed out.