In this paper, we propose a two-stage optimization strategy for solving the Large-scale Traveling Salesman Problems (LSTSPs) named CCPNRL-GA. First, we hypothesize that the participation of a well-performed individual as an elite can accelerate the convergence of optimization. Based on this hypothesis, in the first stage, we cluster the cities and decompose the LSTSPs into multiple subcomponents, and each subcomponent is optimized with a reusable Pointer Network (PtrNet). After subcomponents optimization, we combine all sub-tours to form a valid solution, this solution joins the second stage of optimization with GA. We validate the performance of our proposal on 10 LSTSPs and compare it with traditional EAs. Experimental results show that the participation of an elite individual can greatly accelerate the optimization of LSTSPs, and our proposal has broad prospects for dealing with LSTSPs.

翻译：在本文中,我们提出了一个名为CCPNRL-GA(CCPNRL-GA)的解决大型旅游推销员问题(LSTSPs)的两阶段优化战略。 首先,我们假设业绩良好的个人作为精英的参与能够加快优化的趋同。基于这一假设,在第一阶段,我们把城市集中起来,将LSTSP分解成多个子构件,每个子构件都以可再利用的点子网络(PtrNet)为优化。在子构件优化后,我们把所有次图结合起来,形成一个有效的解决方案,这一解决方案与GA合并到第二阶段。我们验证了我们关于10个LSTSPs的提案的绩效,并将其与传统的EAs进行比较。实验结果表明,精英个人的参与可以大大加快LSTSPs的优化,我们的提案在与LSTSPs打交道方面有着广阔的前景。