Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 3 of 3

Full-Text Articles in Engineering

Blended Biogeography-Based Optimization For Constrained Optimization, Haiping Ma, Daniel J. Simon Apr 2011

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 …


Analytical And Numerical Comparisons Of Biogeography-Based Optimization And Genetic Algorithms., Daniel J. Simon, Rick Rarick, Mehmet Ergezer, Dawei Du Apr 2011

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 …


Intelligent Controls For A Semi-Active Hydraulic Prosthetic Knee, Timothy Allen Wilmot Jan 2011

Intelligent Controls For A Semi-Active Hydraulic Prosthetic Knee, Timothy Allen Wilmot

ETD Archive

We discuss open loop control development and simulation results for a semi-active above-knee prosthesis. The control signal consists of two hydraulic valve settings. These valves control a rotary actuator that provides torque to the prosthetic knee. We develop open loop control using biogeography-based optimization (BBO), which is a recently developed evolutionary algorithm, and gradient descent. We use gradient descent to show that the control generated by BBO is locally optimal. This research contributes to the field of evolutionary algorithms by demonstrating that BBO is successful at finding optimal solutions to complex, real-world, nonlinear, time varying control problems. The research contributes …