A data structure useful for finding Hamiltonian cycles
Theoretical Computer Science
Data structures for traveling salesmen
SODA '93 Selected papers from the fourth annual ACM SIAM symposium on Discrete algorithms
Experiments on traveling salesman heuristics
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Chained Lin-Kernighan for Large Traveling Salesman Problems
INFORMS Journal on Computing
A hybrid heuristic for the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Implementation of an Effective Hybrid GA for Large-Scale Traveling Salesman Problems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An Iterated Local Search Approach for Finding Provably Good Solutions for Very Large TSP Instances
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
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Lin-Kernighan (LK) is the most powerful local search for the Traveling Salesman Problem (TSP). The choice of data structure for tour representation plays a vital role in LK's performance. Binary trees are asymptotically the best tour representation but they perform empirically best only for TSPs with one million or more cities due to a large overhead. Arrays and two-level trees are used for smaller TSPs. This paper proposes a new three-level tree data structure for tour representation. Although this structure is asymptotically not better than the binary tree structure, it performs empirically better than the conventional structures for TSPs having from a thousand to three million cities.