MEDAL Report 2007003
Dependency Trees, Permutations, and Quadratic Assignment Problem
Martin Pelikan, Shigeyoshi Tsutsui, and Rajiv Kalapala  (2007)

Abstract. This paper describes and analyzes an estimation of distribution algorithm based on dependency tree models (dtEDA), which can explicitly encode probabilistic models for permutations. dtEDA is tested on deceptive ordering problems and a number of instances of the quadratic assignment problem. The performance of dtEDA is compared to that of the standard genetic algorithm with the partially matched crossover (PMX) and the linear order crossover (LOX). In the quadratic assignment problem, the robust tabu search is also included in the comparison.

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Missouri Estimation of Distribution Algorithms Laboratory
Department of Mathematics and Computer Science
University of Missouri-St. Louis, St. Louis, MO


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