Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems

Haiping Ma; Daniel J. Simon

doi:10.1145/1830483.1830561

Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems

Haiping Ma, Daniel J. Simon

Shaoxing University, Shaoxing, China

Research output: Other contribution

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.

Original language	American English
DOIs	https://doi.org/10.1145/1830483.1830561
State	Published - Jul 1 2010

Keywords

Evolutionary algorithm
Biogeography-based optimization
Constrained optimization

Disciplines

Electrical and Computer Engineering

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10.1145/1830483.1830561License: CC BY

Biogeography-Based Optimization with Blended Migration for ConstrFinal published version, 1.06 MBLicense: CC BY

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title = "Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems",

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.",

keywords = "Evolutionary algorithm, Biogeography-based optimization, Constrained optimization",

author = "Haiping Ma and Simon, \{Daniel J.\}",

note = "H. Ma and D. Simon. (2010). Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems. Genetic and Evolutionary Computation Conference, 417-418.",

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doi = "10.1145/1830483.1830561",

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AU - Ma, Haiping

AU - Simon, Daniel J.

N1 - H. Ma and D. Simon. (2010). Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems. Genetic and Evolutionary Computation Conference, 417-418.

PY - 2010/7/1

Y1 - 2010/7/1

N2 - 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.

AB - 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.

KW - Evolutionary algorithm

KW - Biogeography-based optimization

KW - Constrained optimization

UR - https://engagedscholarship.csuohio.edu/enece_facpub/184

U2 - 10.1145/1830483.1830561

DO - 10.1145/1830483.1830561

M3 - Other contribution

ER -

Biogeography-Based Optimization with Blended Migration for Constrained Optimization Problems

Abstract

Keywords

Disciplines

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