Agent协商优化问题的快速混沌遗传算法

随着Internet的日益完善和电子商务的普及，如何快速、高效地进行Agent协商是我们必须面对和解决的一个重要问题。文章在Bazaar协商模型下，给出了一种快速混沌遗传算法，该算法首先将混沌机制引入遗传算法，并在搜索中，以具有一定保证的当前最优解为中心不断压缩优化变量的搜索区间，对算法进行加速。这样即克服了遗传算法过早收敛的缺点，又解决了引入混沌后遗传算法收敛慢的问题。仿真实验表明，它是解决Agent协商优化问题的一种快速有效算法。

An Accelerating Chaos Genetic Algorithm to Solve Agent Negotiation Optimization

Agent negotiation is an important problem.How is quick and high-efficient solved the agent negotiation problem?In this paper,we propose an accelerating chaos genetic.In this paper,by the use of the ergodic property of chaos movement,an accelerated chaos optimization genetic algorithm is proposed.This basic principle of this method is that the chaos system is leaded in genetic algorithm.In the course of searching opti-mization point,this method constantly shrinks the searching area of the optimization variable around the center of the best result.Experiments indicate that this method can searches re-sult faster and more efficient to converge upon the optimal nu-merical value in the whole field.