Article

Research of hybrid biogeography based optimization and clonal selection algorithm for numerical optimization

Authors:

Hongwei MoAuthors Info & Claims

ICSI'11: Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I

Pages 390 - 399

Published: 12 June 2011 Publication History

Abstract

The interest of hybridizing different nature inspired algorithms has been growing in recent years. As a relatively new algorithm in this field, Biogeography Based Optimization(BBO) shows great potential in solving numerical optimization problems and some practical problems like TSP. In this paper, we proposed an algorithm which combines Biogeography Based Optimization (BBO) and Clonal Selection Algorithm (BBOCSA). Several benchmark functions are used for comparison among the hybrid and other nature inspired algorithms (BBO, CSA, PSO and GA). Simulation results show that clone selection can enhance the ability of exploration of BBO and the proposed hybrid algorithm has better performance than the other algorithms on some benchmarks.

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Cited By

Nabil E(2016)A Modified Flower Pollination Algorithm for Global OptimizationExpert Systems with Applications: An International Journal10.1016/j.eswa.2016.03.04757:C(192-203)Online publication date: 15-Sep-2016
https://dl.acm.org/doi/10.1016/j.eswa.2016.03.047
Mo HLi ZZhang L(2012)Biogeography based optimization for multi-knapsack problemsProceedings of the 9th international conference on Advances in Neural Networks - Volume Part I10.1007/978-3-642-31346-2_74(659-667)Online publication date: 11-Jul-2012
https://dl.acm.org/doi/10.1007/978-3-642-31346-2_74

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Information & Contributors

Information

Published In

cover image Guide Proceedings

ICSI'11: Proceedings of the Second international conference on Advances in swarm intelligence - Volume Part I

June 2011

634 pages

ISBN:9783642215148

Editors:
Ying Tan
Peking University, Department of Machine Intelligence, Beijing, China
,
Yuhui Shi
Xi'an Jiaotong-Liverpool University, Department of Electrical and Electronic Engineering, Suzhou, China
,
Yi Chai
Chongqing University, Chongqing, China
,
Guoyin Wang
Chongqing University of Posts and Telecommunications, Chongqing, China

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 12 June 2011

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Cited By

Nabil E(2016)A Modified Flower Pollination Algorithm for Global OptimizationExpert Systems with Applications: An International Journal10.1016/j.eswa.2016.03.04757:C(192-203)Online publication date: 15-Sep-2016
https://dl.acm.org/doi/10.1016/j.eswa.2016.03.047
Mo HLi ZZhang L(2012)Biogeography based optimization for multi-knapsack problemsProceedings of the 9th international conference on Advances in Neural Networks - Volume Part I10.1007/978-3-642-31346-2_74(659-667)Online publication date: 11-Jul-2012
https://dl.acm.org/doi/10.1007/978-3-642-31346-2_74

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