qizhiJing / Optimization-and-Performance-Comparison-of-TSP-Using-GA-PSO-and-ACOLinks
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。
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