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A Hybrid-Heuristics Algorithm for k-Minimum Spanning Tree Problems

  • Hideki Katagiri
  • Qingqiang Guo
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 186)

Abstract

A combinatorial optimization problem, namely k-Minimum Spanning Tree Problem (KMSTP), is to find a subtree with exactly k edges in an undirected graph G, such that the sum of edges’ weights is minimal. This chapter provides a Hybrid algorithm using Memetic Algorithm (MA) as a diversification strategy for Tabu Search (TS) to solve KMSTPs. The genetic operator in the proposed MA is based on dynamic programming, which efficiently finds the optimal subtree in a given tree. The experimental results show that the proposed algorithm is superior to several exiting algorithms in terms of solution accuracy and that the algorithm updates some best known solutions that were found by existing algorithms.

Keywords

Combinatorial optimization Hybrid algorithm k-Minimum spanning tree Memetic algorithm Tabu search 

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of System CyberneticsGraduate School of Engineering, Hiroshima UniversityHigashi-HiroshimaJapan
  2. 2.Graduate School of Engineering, Hiroshima UniversityHigashi-HiroshimaJapan

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