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dc.contributor.author Horton, Shea
dc.contributor.author Marshall, John
dc.contributor.author Lewis, John Jack
dc.date.accessioned 2021-04-23T15:34:14Z
dc.date.available 2021-04-23T15:34:14Z
dc.date.issued 2021-04-29
dc.identifier.uri http://hdl.handle.net/11416/541
dc.description Presented at Fiat Lux Spring 2021. en_US
dc.description.abstract The traveling salesman problem (TSP) involves trying to find the optimal path to tour a collection of cities, or vertices of a graph, based on their weights. This would seem simple enough with just a few cities, but when a tour needs to be calculated for hundreds or thousands of cities, the run time becomes completely unmanageable. It is for this reason that there are not any perfectly accurate algorithms to find the optimal path in sufficient polynomial time, but rather heuristics that can find near-optimal paths and weights. Our research revolved around finding the differences between the top heuristics for this problem and determining which would be the best for us to implement. We ended up picking Christofide’s heuristic with a 2-opt algorithm on top of that, guaranteeing us, at worst, to be at 1.5x the length of the optimal path. en_US
dc.publisher Florida Southern College en_US
dc.subject Traveling salesman problem en_US
dc.subject Heuristic algorithms en_US
dc.title Traveling Salesman Heuristics en_US
dc.type Presentation en_US


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