A Memory Adaptive Reasoning Technique for Solving the Capacitated Minimum Spanning Tree Problem

Abstract

In this paper we propose a hybrid memory adaptive heuristic for solving the Capacitated Minimum Spanning Tree (CMST) problem. We augment the problem formulation with additional non-redundant constraints via use of adaptive memory, to improve upon the performance of an elementary heuristic (the Esau-Williams heuristic). Our methodology is tested against many of the previously reported heuristics for the CMST. We conclude that our generalized procedure performs on par with the best of these approaches in terms of solution quality, while expending a very modest amount of computational effort.