基于改进遗传算法的最短路径问题研究

Zongyan Xu, Haihua Li, Ye Guan
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引用次数: 5

摘要

本文研究了网络优化中的最短路径问题,提出了一个带约束的网络优化模型。为了解决这一问题,我们通过遗传算法的最优选择和交叉策略提出了一种改进的遗传算法,并探索了改进遗传算法求解最短路径问题的框架和关键步骤。该算法优化能力强,结构简单,易于处理约束条件,具有智能计算的优点。实验结果证明了改进遗传算法的有效性,表明了算法的搜索效率和解的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on the Shortest Path Problem Based on Improved Genetic Algorithm
This paper adresses a shortest path problem in network optimization, and proposes a model with constraints. In order to solve the problem, we present an improved genetic algorithm through optimal selection and crossover strategy of genetic algorithm, and explore the framework and key steps of improved genetic algorithm for solving shortest path problem. This algorithm with advantages of intelligent computation has the strong optimization ability and simple structure, which can handle the constraints easily. The results of experiment demonstrate the effectiveness of the improved genetic algorithm and show the search efficiency and solution quality of the algorithm.
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