Repositorio de producción científica de la Universidad de Sevilla

Modelo de computación evolutivo para redes sostenibles, eficientes y resistentes.

Opened Access Modelo de computación evolutivo para redes sostenibles, eficientes y resistentes.
Estadísticas
Icon
Exportar a
Autor: Mendes Guerreiro, Pedro Miguel
Director: Márquez Perez, Alberto
Machado Jesús, Mario Carlos
Departamento: Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII)
Fecha: 2017-09-29
Tipo de documento: Tesis Doctoral
Resumen: We present a new approach to adapt the differential evolution (DE) algorithm so that it can be applied in combinatorial optimization problems. The differential evolution algorithm has been proposed as an optimization algorithm for the continuous domain, using real numbers to encode the solutions, and its main operator, the mutation, uses a arithmetic operations to create a mutant using three different random solutions. This mutation operator cannot be used in combinatorial optimization problems, which have a domain of a discrete and finite set of objects. Based on this concept, we present an idea of representing each solution as a set, and replace the arithmetic operators in the classic DE genetic operators by set operators. Using a well known NP-hard problem, the traveling salesman problem (TSP), as an example of a combinatorial optimization problem, we study different possibilities for the mutation operator, presenting the advantages and disadvantages of each, before setting with ...
[Ver más]
Cita: Mendes Guerreiro, P.M. (2017). Modelo de computación evolutivo para redes sostenibles, eficientes y resistentes.. (Tesis Doctoral Inédita). Universidad de Sevilla, Sevilla.
Tamaño: 1.582Mb
Formato: PDF
Tamaño: 6.222Mb
Formato: PDF

URI: http://hdl.handle.net/11441/68599

Mostrar el registro completo del ítem


Esta obra está bajo una Licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional

Este registro aparece en las siguientes colecciones