Traveling Salesman Heuristics

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.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.identifier.uri	http://hdl.handle.net/11416/541
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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