Técnicas de soft-computing para el desarrollo de redes de acceso móvil con control de polución electromagnética

Abstract

This Ph. D Thesis is focused on The Mobile Network Deployment Problem (MNDP) a class of assignment problem in GMS networks. It is usually stated as an optimization problem which looks for a solution with the minimal possible economic cost of the deployment and the maximal possible coverage percentage of the communication network. Thus, in the classical problem, the objective function is ussually defined by both variables: cost and coverage percentage. In this work we include a third variable in the objective function: the electromagnetic radiation due to the base stations working. The society feels some apprehension because the possible negative effects of radiation in human life. The idea of considering the pollution control in the MNDP came up from this social feeling. This new optimization problem is solved through two methods: an evolutive algorithm and a new algorithm recently published: The Coral Reefs Optimization (CRO). It is bio-inspired on the coral reefs behaviour in natural world. The results of both algorithms have been compared with other three algorithms considering the same fitness function. They are: the Particle Swarm Optimization algorithm, the Harmony Search algorithm and a greedy one. Our experiments show that CRO is the best algorithm to solve the MNDP.