Hybrid Approaches based on Simulated Annealing, Tabu Search and Ant Colony Optimization for Solving the k-Minimum Spanning Tree Problem

In graph theory, the k-minimum spanning tree problem is considered to be one of the well-known NP hard problems to solve. This paper address this problem by proposing several hybrid approximate approaches based on the combination of simulated annealing, tabu search and ant colony optimization algori...

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Vydáno v:International journal of advanced computer science & applications Ročník 12; číslo 2
Hlavní autoři: Addou, El Houcine, Serghini, Abelhafid, Bekkaye, El
Médium: Journal Article
Jazyk:angličtina
Vydáno: West Yorkshire Science and Information (SAI) Organization Limited 2021
Témata:
Algorithms
Ant colony optimization
Computer science
Experiments
Graph theory
Methods
Neighborhoods
Optimization algorithms
Simulated annealing
Tabu search
Trees
ISSN:2158-107X, 2156-5570
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Shrnutí:In graph theory, the k-minimum spanning tree problem is considered to be one of the well-known NP hard problems to solve. This paper address this problem by proposing several hybrid approximate approaches based on the combination of simulated annealing, tabu search and ant colony optimization algorithms. The performances of the proposed methods are compared to other approaches from the literature using the same well-known library of benchmark instances.
Bibliografie:ObjectType-Article-1
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ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2021.0120288