Mixtures of Generalized Mallows models for solving the quadratic assignment problem

Abstract

Recently, distance-based exponential probability models have demonstrated their validity in the context of estimation of distribution algorithms when solving permutationbased combinatorial optimisation problems. However, despite their successful performance, some of these models are unimodal, and, therefore, they might not be flexible enough to model the… (More)
DOI: 10.1109/CEC.2015.7257137

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Cite this paper

@article{Ceberio2015MixturesOG, title={Mixtures of Generalized Mallows models for solving the quadratic assignment problem}, author={Josu Ceberio and Roberto Santana and Alexander Mendiburu and Jos{\'e} Antonio Lozano}, journal={2015 IEEE Congress on Evolutionary Computation (CEC)}, year={2015}, pages={2050-2057} }