基于最短路径问题的编码算法

Fanghan Liu, Xiaobing Tang, Zhaohui Yang
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引用次数: 1

摘要

城市交通网络是动态随机的,动态随机最短路径问题是np困难问题。路径优化问题广泛应用于交通、通信和计算机网络等领域。通过对染色体模式进行编码,提出了一种改进的自适应遗传算法。研究了基于遗传算法原理的最短路径问题,并通过调整编码参数对遗传算法进行了改进。大量实验表明,改进的遗传算法在全局优化中比A*算法和Dijkstra算法能更快地适应新的交通方式,在交通运输和计算机网络领域的最短路径问题中获得更好的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Encoding Algorithm Based on the Shortest Path Problem
The transportation network of the city is dynamic and stochastic, The problem of dynamic stochastic shortest path is NP-hard. the optimal problem of path is widely used in the fields of transportation, communication and computer network. An improved self adaptive genetic algorithm is proposed by encoding the chromosomal mode.The paper investigates the shortest path problem based on the genetic algorithm principle, and improved genetic algorithm by adjusting the encoding parameters. Mny experiments indicate that the improved genetic algorithm could adapt to new transportation rapidly in global optimization than A* algorithm and Dijkstra algorithm and obtain the better solutions in the shortest path problem in the fields of transportation and computer network.
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