Abstract
Combinatorial optimization problems with multiple objectives are, in general, more realistic representations of practical situations than their counterparts with a single-objective. The bi-objective minimum spanning tree problem is a NP-hard problem with applications in network design. In this paper a memetic algorithm is presented to solve this problem. A computational experiment compares the proposed approach with AESSEA, a known algorithm of the literature. The comparison of the algorithms is done with basis on the binary additive (-indicator. The results show that the proposed algorithm consistently produces better solutions than the other method.
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Rocha, D.A.M., Goldbarg, E.F.G., Goldbarg, M.C. (2006). A Memetic Algorithm for the Biobjective Minimum Spanning Tree Problem. In: Gottlieb, J., Raidl, G.R. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2006. Lecture Notes in Computer Science, vol 3906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11730095_19
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DOI: https://doi.org/10.1007/11730095_19
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