Document Type
Conference Proceeding
Publication Date
7-2010
Publication Title
GECCO '10 Proceedings of the 12th annual conference on Genetic and Evolutionary Computation
Abstract
Biogeography-based optimization (BBO) is a new evolutionary algorithm based on the science of biogeography. We propose two extensions to BBO. First, we propose blended migration. Second, we modify BBO to solve constrained optimization problems. The constrained BBO algorithm is compared with solutions based on a genetic algorithm (GA) and particle swarm optimization (PSO). Numerical results indicate that BBO generally performs better than GA and PSO in handling constrained single-objective optimization problems.
Repository Citation
Ma, Haiping and Simon, Daniel J., "Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems" (2010). Electrical and Computer Engineering Faculty Publications. 184.
https://engagedscholarship.csuohio.edu/enece_facpub/184
Original Citation
H. Ma and D. Simon. (2010). Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems. Genetic and Evolutionary Computation Conference, 417-418.
DOI
10.1145/1830483.1830561
Version
Publisher's PDF
Publisher's Statement
ACM New York, NY, USA ©2010
Comments
This work was partially supported by the Zhejiang Provincial Natural Science Foundation of China under Grant Y1090866, and by Grant 0826124 from the National Science Foundation.