Abstract
Evolutionary algorithms are applied to problems that are not well understood as well as to problems in combinatorial optimization. The analysis of these search heuristics has been started for some well-known polynomial solvable problems. Such analyses are starting points for the analysis of evolutionary algorithms of difficult problems. We consider the NP-hard multi-objective minimum spanning tree problem and give upper bounds on the expected time until a simple evolutionary algorithm has produced a population including for each extremal point of the Pareto Front a corresponding spanning tree.
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Neumann, F. (2004). Expected Runtimes of a Simple Evolutionary Algorithm for the Multi-objective Minimum Spanning Tree Problem. In: Yao, X., et al. Parallel Problem Solving from Nature - PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, vol 3242. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30217-9_9
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DOI: https://doi.org/10.1007/978-3-540-30217-9_9
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