A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems

Sotirios K. Goudos; Katherine Siakavara; John N. Sahalos

doi:10.1109/HPCSim.2016.7568346

A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems

Sotirios K. Goudos, Katherine Siakavara, John N. Sahalos

Department of Engineering

Aristotle University of Thessaloniki

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Biogeography-Based Optimization (BBO) which is inspired by the science of biogeography, is a stochastic population-based Evolutionary Algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other non-linear migration models have been proposed in the literature. A popular combinatorial optimization problem in antenna design is array thinning. The purpose of this paper to study the performance of these models on antenna array thinning problems. We apply BBO with four different migration models to five different array design cases. The problems dimensions range from 50 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other models. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.

Original language	English
Title of host publication	2016 International Conference on High Performance Computing and Simulation, HPCS 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	270-277
Number of pages	8
ISBN (Electronic)	9781509020881
DOIs	https://doi.org/10.1109/HPCSim.2016.7568346
Publication status	Published - 13 Sept 2016
Event	14th International Conference on High Performance Computing and Simulation, HPCS 2016 - Innsbruck, Austria Duration: 18 Jul 2016 → 22 Jul 2016

Other

Other	14th International Conference on High Performance Computing and Simulation, HPCS 2016
Country/Territory	Austria
City	Innsbruck
Period	18/07/16 → 22/07/16

Keywords

array thinning
biogeography based optimization
evolutionary algorithms
Linear array synthesis
migration models
optimization methods

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10.1109/HPCSim.2016.7568346

Cite this

Goudos, S. K., Siakavara, K., & Sahalos, J. N. (2016). A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems. In 2016 International Conference on High Performance Computing and Simulation, HPCS 2016 (pp. 270-277). Article 7568346 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPCSim.2016.7568346

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title = "A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems",

abstract = "Biogeography-Based Optimization (BBO) which is inspired by the science of biogeography, is a stochastic population-based Evolutionary Algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other non-linear migration models have been proposed in the literature. A popular combinatorial optimization problem in antenna design is array thinning. The purpose of this paper to study the performance of these models on antenna array thinning problems. We apply BBO with four different migration models to five different array design cases. The problems dimensions range from 50 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other models. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.",

keywords = "array thinning, biogeography based optimization, evolutionary algorithms, Linear array synthesis, migration models, optimization methods",

author = "Goudos, {Sotirios K.} and Katherine Siakavara and Sahalos, {John N.}",

year = "2016",

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doi = "10.1109/HPCSim.2016.7568346",

language = "English",

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booktitle = "2016 International Conference on High Performance Computing and Simulation, HPCS 2016",

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Goudos, SK, Siakavara, K & Sahalos, JN 2016, A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems. in 2016 International Conference on High Performance Computing and Simulation, HPCS 2016., 7568346, Institute of Electrical and Electronics Engineers Inc., pp. 270-277, 14th International Conference on High Performance Computing and Simulation, HPCS 2016, Innsbruck, Austria, 18/07/16. https://doi.org/10.1109/HPCSim.2016.7568346

A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems. / Goudos, Sotirios K.; Siakavara, Katherine; Sahalos, John N.
2016 International Conference on High Performance Computing and Simulation, HPCS 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 270-277 7568346.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Sahalos, John N.

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Y1 - 2016/9/13

N2 - Biogeography-Based Optimization (BBO) which is inspired by the science of biogeography, is a stochastic population-based Evolutionary Algorithm (EA). The original BBO uses a linear migration model to describe how species migrate from one island to another. Other non-linear migration models have been proposed in the literature. A popular combinatorial optimization problem in antenna design is array thinning. The purpose of this paper to study the performance of these models on antenna array thinning problems. We apply BBO with four different migration models to five different array design cases. The problems dimensions range from 50 to 300. The results show that BBO with sinusoidal migration model generally performs better than the other models. However, these results are considered to be indicative and do not generally apply to all optimization problems in antenna design.

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A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems

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