Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks
| Autor: | Alejandro Cervantes, Sandra García, Inés M. Galván, Cristobal Luque |
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| Jazyk: | angličtina |
| Rok vydání: | 2009 |
| Předmět: |
Informática
Mathematical optimization education.field_of_study Multiobjective optimization problem Computer science Population Evolutionary algorithm Pareto principle MANETs Hybridation Particle swarm optimization Context (language use) Mobile ad hoc network MOPSO Broadcasting (networking) ESN Mobile ad-hoc networks education Algorithm |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783642024771 IWANN (1) e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid instname |
| Popis: | Proceeding of: 10th InternationalWork-Conference on Artificial Neural Networks, IWANN 2009 Salamanca, Spain, June 10-12, 2009 The aim os this paper is to study the hybridization of two multi-objective algorithms in the context of a real problem, the MANETs problem. The algorithms studied are Particle Swarm Optimization (MOPSO) and a new multiobjective algorithm based in the combination of NSGA-II with Evolution Strategies (ESN). This work analyzes the improvement produced by hybridization over the Pareto’s fronts compared with the non-hybridized algorithms. The purpose of this work is to validate how hybridization of two evolutionary algorithms of different families may help to solve certain problems together in the context of MANETs problem. The hybridization used for this work consists on a sequential execution of the two algorithms and using the final population of the first algorithm as initial population of the second one. This article has been financed by the Spanish founded research MEC projects OPLINK::UC3M, Ref:TIN2005-08818- C04-02 and MSTAR::UC3M, Ref:TIN2008-06491-C04-03. Publicado |
| Databáze: | OpenAIRE |
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