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

• Published in: Soft computing (Berlin, Germany) Vol. 25; no. 16; pp. 11289 - 11305
• Main Authors: Singh, Kavita, Sundar, Shyam
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2021
• Subjects: Application of Soft Computing; Artificial Intelligence; Computational Intelligence; Control; Engineering; Mathematical Logic and Foundations; Mechatronics; Robotics; Neighborhood strategies; Artificial bee colony algorithm; Swarm intelligence; Permutation encoding; Bounded-diameter; Spanning tree
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-021-05913-z

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.