Operadores de recombinação baseados em permutação para representações de grafos

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2017-08-23

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Universidade Federal de Goiás

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The application of Evolutionary Algorithms in the solution of problems characterized by the unviability through deterministic methods, has made this technique a vast object investigated. Its application to Network Design Problems (NDPs), has been specially studied. NDPs are characterized by modeling real world problems related to network design applied to resource distribution, logistics, telecommunications, routing and even social networks. The solution to these problems involves searching for a graph such as trees that meets criteria for cost minimization, availability, scaling among other constraints that make them complex. The application of Evolutionary Agorithms to NDPs requires a Representation that codes solutions properly towards to these problems. The Node-Depth Encoding (NDE) has been studied and presented results that have aroused the attention of researchers in this topic. In this work, we propose the development of a new recombination operator for NDE called NCX, based on the permutation recombination operator CX. In addition, a method is proposed for correction of infeasible solutions due to an invalid depth for a position in the array. The correction method is applied to both NCX, NOX and NPBX. The operators with their methods of correction are validated for the bias and heritability properties and finally are applied to the Bounded Diameter Minimmum Spanning Tree (BDMSTP) through Evolutionary Algorithms developed for this NDP. The results show that the operators have bias towards to star like trees and good heritability of the edges and depths of the vertices. The developed operators also showed competitiveness when applied to the BDMSTP, even surpassing other representations in the quality of the solutions.

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LIMA, R. L. Operadores de recombinação baseados em permutação para representações de grafos. 2017. 81 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2017.