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首页> 外文期刊>Procedia Computer Science >Application of a Genetic Algorithm with Random Crossover and Dynamic Mutation on the Travelling Salesman Problem
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Application of a Genetic Algorithm with Random Crossover and Dynamic Mutation on the Travelling Salesman Problem

机译：带有随机交叉和动态变异的遗传算法在旅行商问题上的应用

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摘要

Travelling salesman problem is a combinatorial optimization problem with wide application background and important theoretical value. The traditional method is only suitable for solving small scale travelling salesman problems, thus limiting the application and popularization of such methods. Based on genetic algorithm, the paper proposes an improved strategy combining random crossover and dynamic mutation to increase population diversity and optimize mutation characters. The simulation results show the convergence rate and the optimal solution of the improved algorithm in the paper are obviously superior to the traditional genetic algorithm, the adaptive crossover probability genetic algorithm and the improved selection genetic algorithm, and it provides a new method for the travelling salesman problem.
机译：旅行商问题是具有广泛应用背景和重要理论价值的组合优化问题。传统方法仅适合解决小规模旅行商问题，从而限制了这种方法的应用和推广。基于遗传算法，提出了一种结合随机交叉和动态突变的改进策略，以增加种群多样性并优化突变特征。仿真结果表明，改进算法的收敛速度和最优解明显优于传统遗传算法，自适应交叉概率遗传算法和改进选择遗传算法，为旅行商提供了一种新方法。问题。

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