A multi-population hybrid biased random key genetic algorithm for hop-constrained trees in nonlinear cost flow networks

Dalila B. M. M. Fontes, José Fernando Gonçalves
2012 Optimization Letters  
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. In this paper we enlarge the application of these types of algorithms by presenting a multi-population hybrid genetic algorithm to another communication design problem. This new problem is modeled through a hop-constrained minimum spanning tree also exhibiting the characteristic of flows. All nodes, except
more » ... or the root node, have a nonnegative flow requirement. 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) and we have termed it hop-constrained minimum cost flow spanning tree problem (HMFST). The efficiency and effectiveness of the proposed method can be seen from the computational results reported.
doi:10.1007/s11590-012-0505-5 fatcat:wckrr7wvpvf7plpx56riqqgbnq