Design of capacitated minimum spanning tree with uncertain cost and demand parameters
The classical Capacitated Minimum Spanning Tree Problem (CMSTP) deals with finding a minimum-cost spanning tree so that the total demand of the vertices in each subtree does not exceed the capacity limitation. In most of the CMSTP models, the edge costs and the demands of the vertices in the network are assumed to be known with certainty. This paper considers the CMSTP model, where the edge costs and/or the demands are only approximately known. A fast approximate reasoning algorithm, which is based on the EsauWilliams savings heuristic and fuzzy logic rules, is proposed. The computational results of the study based on the proposed approach are also reported.
fuzzy logic capacitated minimal spanning tree problem esauwilliams heuristic fuzzy algorithm simulation