基于正态分布的改进遗传算法求解旅行商问题

2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2018-08-01 DOI:10.1109/ICVRIS.2018.00094

Ying Gao, Jianwei Ye

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引用次数: 1

摘要

传统遗传算法采用普通随机数作为遗传因子交换和变异的选择条件。受weed算法的启发，采用正态分布序列作为随机数库。每次从该库中读取遗传因子的交换和变异位置，并将其应用于求解旅行商问题。Matlab测试表明，该方法可以提高收敛速度，提高收敛精度。

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An Improved Genetic Algorithm Based on Normal Distribution for Solving the Traveling Salesman Problem

Traditional genetic algorithm uses ordinary random number as the selection condition of exchange and variation of genetic factors.Inspired by the weed algotithm, the normal distribution sequence is used as a random number library. The location of exchange and variation of genetic factors is read from this library every time and applied to solve the traveling salesman problem.Matlab test shows that this method can improve convergence speed and improve convergence accuracy.

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2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)

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