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Full-Text Articles in Engineering
Analytical And Numerical Comparisons Of Biogeography-Based Optimization And Genetic Algorithms., Daniel J. Simon, Rick Rarick, Mehmet Ergezer, Dawei Du
Analytical And Numerical Comparisons Of Biogeography-Based Optimization And Genetic Algorithms., Daniel J. Simon, Rick Rarick, Mehmet Ergezer, Dawei Du
Electrical and Computer Engineering Faculty Publications
We show that biogeography-based optimization (BBO) is a generalization of a genetic algorithm with global uniform recombination (GA/GUR). Based on the common features of BBO and GA/GUR, we use a previously-derived BBO Markov model to obtain a GA/GUR Markov model. One BBO characteristic which makes it distinctive from GA/GUR is its migration mechanism, which affects selection pressure (i.e., the probability of retaining certain features in the population from one generation to the next). We compare the BBO and GA/GUR algorithms using results from analytical Markov models and continuous optimization benchmark problems. We show that the unique selection pressure provided by …
Blended Biogeography-Based Optimization For Constrained Optimization, Haiping Ma, Daniel J. Simon
Blended Biogeography-Based Optimization For Constrained Optimization, Haiping Ma, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography-based optimization (BBO) is a new evolutionary optimization method that is based on the science of biogeography. We propose two extensions to BBO. First, we propose a blended migration operator. Benchmark results show that blended BBO outperforms standard BBO. Second, we employ blended BBO to solve constrained optimization problems. Constraints are handled by modifying the BBO immigration and emigration procedures. The approach that we use does not require any additional tuning parameters beyond those that are required for unconstrained problems. The constrained blended BBO algorithm is compared with solutions based on a stud genetic algorithm (SGA) and standard particle swarm …
Biogeography-Based Optimization Of Neuro-Fuzzy System Parameters For Diagnosis Of Cardiac Disease, Mirela Ovreiu, Daniel J. Simon
Biogeography-Based Optimization Of Neuro-Fuzzy System Parameters For Diagnosis Of Cardiac Disease, Mirela Ovreiu, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Cardiomyopathy refers to diseases of the heart muscle that becomes enlarged, thick, or rigid. These changes affect the electrical stability of the myocardial cells, which in turn predisposes the heart to failure or arrhythmias. Cardiomyopathy in its two common forms, dilated and hypertrophic, implies enlargement of the atria; therefore, we investigate its diagnosis through P wave features. In particular, we design a neuro-fuzzy network trained with a new evolutionary algorithm called biogeography-based optimization (BBO). The neuro-fuzzy network recognizes and classifies P wave features for the diagnosis of cardiomyopathy. In addition, we incorporate opposition-based learning in the BBO algorithm for improved …
Biogeography-Based Optimization With Blended Migration For Constrained Optimization Problems, Haiping Ma, Daniel J. Simon
Biogeography-Based Optimization With Blended Migration For Constrained Optimization Problems, Haiping Ma, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
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.