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Solving the Large-Scale TSP Problem in 1 h: Santa Claus Challenge 2020

Radu Mariescu-Istodor, Pasi Fränti

2021Frontiers in Robotics and AI23 citationsDOIOpen Access PDF

Abstract

The scalability of traveling salesperson problem (TSP) algorithms for handling large-scale problem instances has been an open problem for a long time. We arranged a so-called Santa Claus challenge and invited people to submit their algorithms to solve a TSP problem instance that is larger than 1 M nodes given only 1 h of computing time. In this article, we analyze the results and show which design choices are decisive in providing the best solution to the problem with the given constraints. There were three valid submissions, all based on local search, including k -opt up to k = 5. The most important design choice turned out to be the localization of the operator using a neighborhood graph. The divide-and-merge strategy suffers a 2% loss of quality. However, via parallelization, the result can be obtained within less than 2 min, which can make a key difference in real-life applications.

Topics & Concepts

Merge (version control)Computer scienceScalabilityTravelling salesman problemGraphOperator (biology)Key (lock)Mathematical optimizationTheoretical computer scienceAlgorithmParallel computingMathematicsDatabaseComputer securityBiochemistryGeneRepressorChemistryTranscription factorVehicle Routing Optimization MethodsMetaheuristic Optimization Algorithms ResearchRobotic Path Planning Algorithms
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