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

作者：Fontes Dalila B M M^*; Goncalves Jose Fernando

来源：Optimization Letters, 2013, 7(6): 1303-1324.

DOI：10.1007/s11590-012-0505-5

• Multi-population
• Genetic algorithms
• Local search
• Network flows
• Hop-constrained trees
• General nonlinear costs

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 for 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 and we have termed it hop-constrained minimum cost flow spanning tree problem. The efficiency and effectiveness of the proposed method can be seen from the computational results reported.

• 出版日期2013-8