Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 8 of 8
Full-Text Articles in Engineering
Analysis Of Migration Models Of Biogeography-Based Optimization Using Markov Theory, Haiping Ma, Daniel J. Simon
Analysis Of Migration Models Of Biogeography-Based Optimization Using Markov Theory, Haiping Ma, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography-based optimization (BBO) is a new evolutionary algorithm inspired by biogeography, which involves the study of the migration of biological species between habitats. Previous work has shown that various migration models of BBO result in significant changes in performance. Sinusoidal migration models have been shown to provide the best performance so far. Motivated by biogeography theory and previous results, in this paper a generalized sinusoidal migration model curve is proposed. A previously derived BBO Markov model is used to analyze the effect of migration models on optimization performance, and new theoretical results which are confirmed with simulation results are obtained. …
The Eigenvalues Of A Tridiagonal Matrix In Biogeography, Boris Igelnik, Daniel J. Simon
The Eigenvalues Of A Tridiagonal Matrix In Biogeography, Boris Igelnik, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
We derive the eigenvalues of a tridiagonal matrix with a special structure. A conjecture about the eigenvalues was presented in a previous paper, and here we prove the conjecture. The matrix structure that we consider has applications in biogeography theory.
A Probabilistic Analysis Of A Simplified Biogeography-Based Optimization Algorithm, Daniel J. Simon
A Probabilistic Analysis Of A Simplified Biogeography-Based Optimization Algorithm, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography-based optimization (BBO) is a population-based evolutionary algorithm (EA) that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. We present a simplified version of BBO and perform an approximate analysis of the BBO population using probability theory. Our analysis provides approximate values for the expected number of generations before the population's best solution improves, and the expected amount of improvement. These expected values are functions of the population size. We quantify three behaviors as the population size increases: first, we see that the best solution in the initial randomly generated …
Fuzzy Robot Controller Tuning With Biogeography-Based Optimization, George Thomas, Paul Lozovyy, Daniel J. Simon
Fuzzy Robot Controller Tuning With Biogeography-Based Optimization, George Thomas, Paul Lozovyy, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography-based optimization (BBO) is an evolutionary algorithm (EA) based upon the models of biogeography, which describe the relationship between habitat suitability and the migration of species across habitats. In this work, we apply BBO to the problem of tuning the fuzzy tracking controller of mobile robots. This is an extension of previous work, in which we used BBO to tune a proportional-derivative (PD) controller for these robots. We show that BBO can successfully tune the shape of membership functions for a fuzzy controller with both simulation and real world experimental results.
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.