Evolutionary selection in simulation-based optimization

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Abstract

In this work we examine the effect of elitist and non-elitist selection on a supply chain problem. The problem is characterized by an output constraint which in turn separates the search space in a feasible and a non-feasible region. Additionally the simulation output is noisy due to a stochastic demand model. We will show analyze which strategy is able to perform a walk on the boundary between the feasible and infeasible space. Additionally a new selection scheme is introduced based on a statistical test to evaluate the difference between two solutions given a number of noisy quality values. This selection scheme is described and evaluated on the problem situation. © 2009 Springer-Verlag Berlin Heidelberg.

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Beham, A., Kofler, M., Affenzeller, M., & Wagner, S. (2009). Evolutionary selection in simulation-based optimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5717 LNCS, pp. 761–768). https://doi.org/10.1007/978-3-642-04772-5_98

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