粒子动力学演化算法及其在求解SOP上的应用  

A Particle Dynamical Evolutionary Algorithm and Its Application on Solving Single-Object Problems

作　　者：李康顺[1,2] 李元香[1] 汤铭端[3] 郑波尽[1] 

机构地区：[1]武汉大学软件工程国家重点实验室 [2]江西理工大学信息工程学院,江西341000 [3]航天科工集团第二研究院

出　　处：《系统仿真学报》2005年第3期595-598,共4页Journal of System Simulation

基　　金：国家自然科学基金项目(60473014);高等学校博士学科点专项科研基金项目(20030486049)

摘　　要：根据粒子输运理论中粒子相空间能量最小原理和熵增法则提出一类粒子动力学演化算法,并在数据实验中用该算法求解了一些传统演化算法难于求解的单目标优化问题(SOP),比如求解凸函数和多峰函数等最小优化问题。由于这种新的动力学演化算法能使几乎所有的个体参加杂交和变异,因此,与传统的演化算法相比,该方法不仅能较快速地求解线性和非线性优化问题,而且还能容易地求出达到最优解的多个坐标点。A particle dynamic evolutionary algorithm is presented based on particle transportation theory according to the principle of energy minimization and the law of entropy increasing in phase space of particles, and in the numerical experiments, we have used this algorithm to solve the single-object optimization problem (SOP), which the traditional evolutionary algorithm is difficult to solve. Compared with the traditional evolutionary algorithm, this algorithm not only can solve linear and non-linear optimization problems more quickly, but also can more easily solve the all coordinates reached the global solution of problems.

关 键 词：演化算法 粒子动力学 输运理论 单目标优化问题 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]