Savings based ant colony optimization for the capacitated minimum spanning tree problem

Marc Reimann*, Marco Laumanns

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)

Abstract

The problem of connecting a set of client nodes with known demands to a root node through a minimum cost tree network, subject to capacity constraints on all links is known as the capacitated minimum spanning tree (CMST) problem. As the problem is NP-hard, we propose a hybrid ant colony optimization (ACO) algorithm to tackle it heuristically. The algorithm exploits two important problem characteristics: (i) the CMST problem is closely related to the capacitated vehicle routing problem (CVRP), and (ii) given a clustering of client nodes that satisfies capacity constraints, the solution is to find a MST for each cluster, which can be done exactly in polynomial time. Our ACO exploits these two characteristics of the CMST by a solution construction originally developed for the CVRP. Given the CVRP solution, we then apply an implementation of Prim's algorithm to each cluster to obtain a feasible CMST solution. Results from a comprehensive computational study indicate the efficiency and effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)1794-1822
Number of pages29
JournalComputers and Operations Research
Volume33
Issue number6
Early online date1 Jan 2005
DOIs
Publication statusPublished - Jun 2006

Fingerprint Dive into the research topics of 'Savings based ant colony optimization for the capacitated minimum spanning tree problem'. Together they form a unique fingerprint.

Cite this