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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/18973
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dc.contributor.authorFarswan P.-
dc.contributor.authorBansal J.C.-
dc.contributor.authorDeep, K.-
dc.contributor.editorGeem Z.W.-
dc.contributor.editorKim J.H.-
dc.date.accessioned2020-12-03T06:29:37Z-
dc.date.available2020-12-03T06:29:37Z-
dc.date.issued2016-
dc.identifier.citationProceedings of Advances in Intelligent Systems and Computing, (2016), 227- 238-
dc.identifier.isbn9.78E+12-
dc.identifier.issn21945357-
dc.identifier.urihttps://doi.org/10.1007/978-3-662-47926-1_22-
dc.identifier.urihttp://repository.iitr.ac.in/handle/123456789/18973-
dc.description.abstractBiogeography based optimization (BBO) has recently gain interest of researchers due to its efficiency and existence of very few parameters. The BBO is inspired by geographical distribution of species within islands. However, BBO has shown its wide applicability to various engineering optimization problems, the original version of BBO sometimes does not perform up to themark. Poor balance of exploration and exploitation is the reason behind it. Migration, mutation and elitism are three operators in BBO. Migration operator is responsible for the information sharing among candidate solutions (islands). In this way, the migration operator plays an important role for the design of an efficient BBO. This paper proposes a new migration operator in BBO. The so obtained BBO shows better diversified search process and hence finds solutions more accurately with high convergence rate. The BBO with new migration operator is tested over 20 test problems. Results are compared with that of original BBO and Blended BBO. The comparison which is based on efficiency, reliability and accuracy shows that proposed migration operator is competitive to the present one. © Springer-Verlag Berlin Heidelberg 2016.-
dc.language.isoen_US-
dc.publisherSpringer Verlag-
dc.relation.ispartofProceedings of Advances in Intelligent Systems and Computing-
dc.subjectBiogeography based optimization-
dc.subjectBlended BBO-
dc.subjectMigration operator-
dc.subjectAlgorithms-
dc.subjectEcology-
dc.subjectEfficiency-
dc.subjectGeographical distribution-
dc.subjectHeuristic algorithms-
dc.subjectLearning algorithms-
dc.subjectBalance of exploration and exploitation-
dc.subjectBiogeography-based optimizations-
dc.subjectBiogeographybased optimizations (BBO)-
dc.subjectBlended BBO-
dc.subjectConvergence rates-
dc.subjectEngineering optimization problems-
dc.subjectInformation sharing-
dc.subjectMigration operator-
dc.subjectOptimization-
dc.titleA modified biogeography based optimization-
dc.typeConference Paper-
dc.scopusid56595259000-
dc.scopusid57189656835-
dc.scopusid8561208900-
dc.affiliationFarswan, P., South Asian University, New Delhi, India-
dc.affiliationBansal, J.C., South Asian University, New Delhi, India-
dc.affiliationDeep, K., Indian Institute of Technology Roorkee, Roorkee, India-
dc.description.correspondingauthorBansal, J.C.; South Asian UniversityIndia-
dc.identifier.conferencedetails2nd International Conference on Harmony Search Algorithm, ICHSA 2015, 19-21 August 2015-
Appears in Collections:Conference Publications [MA]

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