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EOR
2006

A random-key genetic algorithm for the generalized traveling salesman problem

9 years 1 months ago
A random-key genetic algorithm for the generalized traveling salesman problem
The Generalized Traveling Salesman Problem is a variation of the well known Traveling Salesman Problem in which the set of nodes is divided into clusters; the objective is to find a minimum-cost tour passing through one node from each cluster. We present an effective heuristic for this problem. The method combines a genetic algorithm (GA) with a local tour improvement heuristic. Solutions are encoded using random keys, which circumvent the feasibility problems encountered when using traditional GA encodings. On a set of 41 standard test problems with symmetric distances and up to 442 nodes, the heuristic found solutions that were optimal in most cases and were within 1% of optimality in all but the largest problems, with computation times generally within 10 seconds. The heuristic is competitive with other heuristics published to date in both solution quality and computation time.
Lawrence V. Snyder, Mark S. Daskin
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where EOR
Authors Lawrence V. Snyder, Mark S. Daskin
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