加权顶点着色的蒙特卡罗树搜索
On Monte Carlo Tree Search for Weighted Vertex Coloring
摘要：
本文首次研究了利用流行的蒙特卡罗树搜索（MCTS）方法结合专用算法求解加权顶点着色问题。从基本的MCTS算法开始，我们逐渐引入了一些算法变体，其中MCTS通过各种模拟策略（包括贪婪和局部搜索策略）进行扩展。我们对知名的基准实例进行实验，以评估每个研究组合的价值。我们还提供了经验证据，阐明每种策略的优势和局限性。
英文摘要：
This work presents the first study of using the popular Monte Carlo Tree Search (MCTS) method combined with dedicated heuristics for solving the Weighted Vertex Coloring Problem. Starting with the basic MCTS algorithm, we gradually introduce a number of algorithmic variants where MCTS is extended by various simulation strategies including greedy and local search heuristics. We conduct experiments on well-known benchmark instances to assess the value of each studied combination. We also provide empirical evidence to shed light on the advantages and limits of each strategy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
