A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems

DOI10.1515/math-2016-0066zbMath1354.94016OpenAlexW2532947169MaRDI QIDQ330333

Sotirios K. Goudos

Publication date: 25 October 2016

Published in: Open Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/math-2016-0066

zbMATH Keywords

combinatorial optimizationevolutionary algorithmsOFDMbiogeography-based optimization (BBO)PAPRopposition based learningPTS

Mathematics Subject Classification ID

Computational learning theory (68Q32) Analysis of algorithms (68W40) Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Modulation and demodulation in information and communication theory (94A14)

Uses Software

• ABC

Cites Work

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• Probabilistic properties of fitness-based quasi-reflection in evolutionary algorithms
• Analytical and numerical comparisons of biogeography-based optimization and genetic algorithms
• Two-stage update biogeography-based optimization using differential evolution algorithm (DBBO)
• Oppositional concepts in computational intelligence
• An analysis of the equilibrium of migration models for biogeography-based optimization
• A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 special session on real parameter optimization
• A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm
• Cross-Entropy-Based Sign-Selection Algorithms for Peak-to-Average Power Ratio Reduction of OFDM Systems

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