Extending the Front: Designing RFID Antennas Using Multiobjective Differential Evolution with Biased Population Selection | Zendy

James Montgomery | Zendy; Marcus Randall | Zendy; Andrew Lewis | Zendy

Open Access

Extending the Front: Designing RFID Antennas Using Multiobjective Differential Evolution with Biased Population Selection

Author(s) -

James Montgomery,

Marcus Randall,

Andrew Lewis

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.05.174

Subject(s) - computer science , selection (genetic algorithm) , differential evolution , solver , mathematical optimization , multi objective optimization , population , work (physics) , space (punctuation) , differential (mechanical device) , algorithm , artificial intelligence , mathematics , machine learning , aerospace engineering , physics , demography , sociology , engineering , thermodynamics , programming language , operating system

RFID antennas are ubiquitous, so exploring the space of high efficiency and low resonant frequency antennas is an important multiobjective problem. Previous work has shown that the continuous solver differential evolution (DE) can be successfully applied to this discrete problem, but has difficulty exploring the region of solutions with lowest resonant frequency. This paper introduces a modified DE algorithm that uses biased selection from an archive of solutions to direct the search toward this region. Results indicate that the proposed approach produces superior attainment surfaces to the earlier work. The biased selection procedure is applicable to other population-based approaches for this problem

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