The goal of thiswork is to maintain a high level of solution quality while simplifying the overall algorithm.Boufar, TarekUniv. Littoral Côte d’Opale, LISICRifki, OmarUniv. Littoral Côte d’Opale, LISICBasseur, MatthieuUniv. Littoral Côte d’Opale, LISIC...
The Lin-Kernighan-Helsgaun (LKH) algorithm is one of the most successful search algorithms for the Traveling Salesman Problem (TSP). The core of LKH is a variable depth local search heuristic...doi:10.1007/978-3-319-99253-2_8Renato Tinós...
solving the equality generalized traveling salesman problem using the lin–kernighan–helsgaun algorithm.pdf 2017-01-19上传 solving the equality generalized traveling salesman problem using the lin–kernighan–helsgaun algorithm 文档格式: .pdf 文档大小: ...
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman ProblemJiongzhi ZhengKun HeJianrong ZhouYan JinChu-Min LiNational Conference on Artificial Intelligence
The Sharpened No Free Lunch theorem applies to black box optimization and states that no arbitrarily selected algorithm is better than another when the algorithms are compared over sets of functions that are closed under permutation. Focused No Free Lunch theorems look at comparisons of specific ...
Lin, S., Kernighan, B.W.: An effective heuristic algorithm for the traveling salesman problem. Oper. Res. 21(2), 498–516 (1973) Article MathSciNet Google Scholar Reinelt, G.: TSPLIB—a traveling salesman problem library. ORSA J. Comput. 3(4), 376–384 (1991) Article MATH Google...