@inproceedings{
 title = {A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems},
 type = {inproceedings},
 year = {2016},
 keywords = {Linear array synthesis,array thinning,biogeography based optimization,evolutionary algorithms,migration models,optimization methods},
 pages = {270-277},
 id = {c443f0a9-c008-3c88-81c2-554dc64b79e4},
 created = {2020-02-29T16:57:42.381Z},
 file_attached = {false},
 profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},
 last_modified = {2023-02-11T18:54:02.985Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Goudos2016e},
 private_publication = {false},
 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.},
 bibtype = {inproceedings},
 author = {Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.},
 doi = {10.1109/HPCSim.2016.7568346},
 booktitle = {2016 International Conference on High Performance Computing and Simulation, HPCS 2016}
}

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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.","bibtype":"inproceedings","author":"Goudos, Sotirios K. and Siakavara, Katherine and Sahalos, John N.","doi":"10.1109/HPCSim.2016.7568346","booktitle":"2016 International Conference on High Performance Computing and Simulation, HPCS 2016","bibtex":"@inproceedings{\n title = {A comparative study of different biogeography based optimization migration models performance on antenna array thinning problems},\n type = {inproceedings},\n year = {2016},\n keywords = {Linear array synthesis,array thinning,biogeography based optimization,evolutionary algorithms,migration models,optimization methods},\n pages = {270-277},\n id = {c443f0a9-c008-3c88-81c2-554dc64b79e4},\n created = {2020-02-29T16:57:42.381Z},\n file_attached = {false},\n profile_id = {c69aa657-d754-373c-91b7-64154b7d5d91},\n last_modified = {2023-02-11T18:54:02.985Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Goudos2016e},\n private_publication = {false},\n abstract = {Biogeography-Based Optimization (BBO) which is inspired by the science of biogeography, is a stochastic population-based Evolutionary Algorithm (EA). 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