A multi-objective evolutionary approach for the antenna positioning problem

Authors:
Carlos Segura;Yanira González;Gara Miranda;Coromoto León
Affiliations:
Dpto. Estadística, I.O. y Computación, Universidad de La Laguna, La Laguna, Santa Cruz de Tenerife, Spain;Dpto. Estadística, I.O. y Computación, Universidad de La Laguna, La Laguna, Santa Cruz de Tenerife, Spain;Dpto. Estadística, I.O. y Computación, Universidad de La Laguna, La Laguna, Santa Cruz de Tenerife, Spain;Dpto. Estadística, I.O. y Computación, Universidad de La Laguna, La Laguna, Santa Cruz de Tenerife, Spain
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Year:
2010

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Abstract

Antenna Positioning Problem (app) is an NP-Complete Optimisation Problem which arises in the telecommunication field. It consists in identifying the infrastructures required to establish a wireless network. Several objectives must be considered when tackling app: minimise the cost, and maximise the coverage, among others. Most of the proposals simplify the problem, converting it into a mono-objective problem. In this work, multi-objective evolutionary algorithms are used to solve app. In order to validate such strategies, computational results are compared with those obtained by means of mono-objective algorithms. An extensive comparison of several evolutionary algorithms and variation operators is performed. Results show the advantages of incorporating problem-dependent information into the evolutionary strategies. Also, they show the importance of properly tuning the evolutionary approaches.