Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Engineering
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.
A Majorization Algorithm For Constrained Correlation Matrix Approximation, Daniel J. Simon, Jeff Abell
A Majorization Algorithm For Constrained Correlation Matrix Approximation, Daniel J. Simon, Jeff Abell
Electrical and Computer Engineering Faculty Publications
We desire to find a correlation matrix of a given rank that is as close as possible to an input matrix R, subject to the constraint that specified elements in must be zero. Our optimality criterion is the weighted Frobenius norm of the approximation error, and we use a constrained majorization algorithm to solve the problem. Although many correlation matrix approximation approaches have been proposed, this specific problem, with the rank specification and the constraints, has not been studied until now. We discuss solution feasibility, convergence, and computational effort. We also present several examples.