Worst Case Analyses of Nearest Neighbor Heuristicfor Finding the Minimum Weight k - cycle
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Creator Piyashat Sripratak
Title Worst Case Analyses of Nearest Neighbor Heuristicfor Finding the Minimum Weight k - cycle
Contributor Tanapat Chalarux
Publisher King Mongkut's Institute of Technology Ladkrabang
Publication Year 2563
Journal Title Current Applied Science and Technology
Journal Vol. 20
Journal No. 2
Page no. 178-185
Keyword minimum weight k - cycle, worst case analysis, nearest neighbor heuristic
URL Website https://www.tci-thaijo.org/index.php/cast
Website title https://www.tci-thaijo.org/index.php
ISSN 2586-9396
Abstract Given a weighted complete graph ( , w), where w is an edge weight function, the minimum weight k - cycle problem is to find a cycle of k vertices whose total weight is minimum among all k - cycles. Traveling salesman problem (TSP) is a special case of this problem when k = n. Nearest neighbor algorithm (NN) is a popular greedy heuristic for TSP that can be applied to this problem. To analyze the worst case of the NN for the minimum weight k - cycle problem, we prove that it is impossible for the NN to have an approximation ratio. An instance of the minimum weight k - cycle problem is given, in which the NN finds a k - cycle whose weight is worse than the average value of the weights of all k - cycles in that instance. Moreover, the domination number of the NN when k = n and its upper bound for the case k = n 1 is established.
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