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Title of Journal: Nat Comput

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Abbravation: Natural Computing

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Springer Netherlands

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DOI

10.1016/j.ambp.2005.11.002

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1572-9796

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Minimum spanning trees made easier via multiobjec

Authors: Frank Neumann Ingo Wegener
Publish Date: 2006/04/27
Volume: 5, Issue: 3, Pages: 305-319
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Abstract

Many realworld problems are multiobjective optimization problems and evolutionary algorithms are quite successful on such problems Since the task is to compute or approximate the Pareto front multiobjective optimization problems are considered as more difficult than singleobjective problems One should not forget that the fitness vector with respect to more than one objective contains more information that in principle can direct the search of evolutionary algorithms Therefore it is possible that a singleobjective problem can be solved more efficiently via a generalized multiobjective model of the problem That this is indeed the case is proved by investigating the computation of minimum spanning trees

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