Artificial bee colony algorithm using permutation encoding for the bounded diameter minimum spanning tree problem

The bounded diameter minimum spanning tree (BD-MST) problem seeks a spanning tree ( T ) of minimum weight on a given connected, undirected and edge-weighted graph subject to the diameter of T does not exceed D ≥ 2 , where D is a given positive integer. The BD-MST problem is N P -hard problem and fin...

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Published inSoft computing (Berlin, Germany) Vol. 25; no. 16; pp. 11289 - 11305
Main Authors Singh, Kavita, Sundar, Shyam
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2021
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ISSN1432-7643
1433-7479
DOI10.1007/s00500-021-05913-z

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Abstract The bounded diameter minimum spanning tree (BD-MST) problem seeks a spanning tree ( T ) of minimum weight on a given connected, undirected and edge-weighted graph subject to the diameter of T does not exceed D ≥ 2 , where D is a given positive integer. The BD-MST problem is N P -hard problem and finds many real-world applications. In this paper, we propose an artificial bee colony (ABC) algorithm for the BD-MST problem. ABC algorithm is a swarm-based metaheuristic technique based on the intelligent foraging behavior of honeybees. The proposed ABC algorithm employs permutation encoding. To exploit this encoding structure, two neighborhood strategies that help ABC algorithm in faster convergence towards finding high quality solutions are applied. On a set of Euclidean and non-Euclidean benchmark instances for various diameter bounds, the proposed approach has been compared with state-of-the-art approaches. Computational results demonstrate the effectiveness of the proposed approach to the other extant approaches in the literature.
AbstractList The bounded diameter minimum spanning tree (BD-MST) problem seeks a spanning tree ( T ) of minimum weight on a given connected, undirected and edge-weighted graph subject to the diameter of T does not exceed D ≥ 2 , where D is a given positive integer. The BD-MST problem is N P -hard problem and finds many real-world applications. In this paper, we propose an artificial bee colony (ABC) algorithm for the BD-MST problem. ABC algorithm is a swarm-based metaheuristic technique based on the intelligent foraging behavior of honeybees. The proposed ABC algorithm employs permutation encoding. To exploit this encoding structure, two neighborhood strategies that help ABC algorithm in faster convergence towards finding high quality solutions are applied. On a set of Euclidean and non-Euclidean benchmark instances for various diameter bounds, the proposed approach has been compared with state-of-the-art approaches. Computational results demonstrate the effectiveness of the proposed approach to the other extant approaches in the literature.
Author Singh, Kavita
Sundar, Shyam
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  organization: Department of Computer Applications, National Institute of Technology Raipur
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Issue 16
Keywords Neighborhood strategies
Artificial bee colony algorithm
Swarm intelligence
Permutation encoding
Bounded-diameter
Spanning tree
Language English
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SubjectTerms Application of Soft Computing
Artificial Intelligence
Computational Intelligence
Control
Engineering
Mathematical Logic and Foundations
Mechatronics
Robotics
Title Artificial bee colony algorithm using permutation encoding for the bounded diameter minimum spanning tree problem
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