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A Multi Population Genetic Algorithm for Hop-Constrained Trees in Nonlinear Cost Flow Networks

Genetic algorithms and other evolutionary algorithms have been successfully applied to solve constrained minimum spanning tree problems in a variety of communication network design problems. Here we propose a multi population genetic algorithm for yet another communication design problem. The new problem is modeled through a hop-constrained minimum spanning tree also exhibiting the characteristic of flows. In addition to the fixed charge costs, nonlinear flow dependent costs are also considered. This problem is an extension of the well know NP-hard hop-constrained Minimum Spanning Tree problem (HMST). The efficiency and effectiveness of the proposed method can be seen from the computational results reported.