Optimal TSP tour length estimation using Sammon maps

Kou, Shuhan; Golden, Bruce L.; Poikonen, Stefan

doi:10.1007/s11590-022-01937-y

Cited by 1 publication

(1 citation statement)

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“…The points on the boundary of their convex hull are used to initiate a sub-tour onto which the remaining points are added in order of cheapest insertion, similar to the . While recently MDS has been applied to the non-Euclidean TSP for tour length estimation, local clustering, and to understand human cognition [33]- [35], this is the first instance of its use to initiate the CHCI heuristic for the non-Euclidean TSP.…”

Section: Introductionmentioning

confidence: 99%

Optimal Path Planning Through a Sequence of Waypoints

Goutham

Boyle

Menon

et al. 2023

IEEE Robot. Autom. Lett.

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The convex hull cheapest insertion heuristic is known to generate good solutions to the Euclidean Traveling Salesperson Problem. This paper presents an adaptation of this heuristic to the non-Euclidean version of the problem and further extends it to the problem with precedence constraints, also known as the Sequential Ordering Problem. To test the proposed algorithm, the well-known TSPLIB benchmark dataset is modified in a replicable manner to create non-Euclidean instances and precedence constraints. The proposed algorithm is shown to outperform the commonly used Nearest Neighbor algorithm in 97% of the cases that do not have precedence constraints. When precedence constraints exist such that the child nodes are centrally located, the algorithm again outperforms the Nearest Neighbor algorithm in 98% of the studied instances. Considering all spatial layouts of precedence constraints, the algorithm outperforms the Nearest Neighbor heuristic 68% of the time.

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Section: Introductionmentioning

confidence: 99%