旅行商问题（TSP）是一种具有重要优化意义的 NP-hard 问题，广泛应用于运输设计、物流调度和旅游路线规划等领域。为解决该问题，本文采用遗传算法（Genetic Algorithm，GA）、粒子群优化算法（Particle Swarm Optimization，PSO）和蚁群优化算法（Ant Colony Optimization，ACO）进行了对比研究。通过数值实验，本文评估了三种算法在路径长度和收敛性能方面的表现。结果显示，PSO 在收敛速度上具有显著优势，ACO 在解的稳定性和全局搜索能力方面表现优越，而 GA 在最终路径质量上表现最佳。基于这些分析，本文提出了三种算法在实际应用场景中的选择建议。
☆17Dec 16, 2024Updated last year
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