Abstract
The Traveling Salesman Problem, at the heart of many routing applications, has a few well-known relaxations that have been very effective to compute lower bounds on the objective function or even to perform cost-based domain filtering in constraint programming models. We investigate other ways of using such relaxations based on computing the frequency of edges in near-optimal solutions to a relaxation. We report early empirical results on symmetric instances from tsplib.
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Coste, P., Lodi, A., Pesant, G. (2019). Using Cost-Based Solution Densities from TSP Relaxations to Solve Routing Problems. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_12
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