Numerical Methods for Constrained and Unconstrained Optimization.
Abstract
The main thrust of the research has been toward the development of efficient algorithms for solving the finite - dimensional constrained optimization problem. Historically, problems of this type have been solved by either penalty function methods or through linearization procedures. The fact that neither of these techniques is completely satisfactory for general nonlinear problems has lead to a concentrated research effort to find better approaches. What has so far emerged from this work is a blending of the penalty function land linearization ideas with the quadratic approximation methods associated with unconstrained optimization. While there remain many unresolved issues, it is now apparent that this synthesis has resulted in more efficient algorithms for the nonlinear constrained optimization problem. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Dec 23, 1982
- Accession Number
- ADA122912
Entities
People
- Jon W. Tolle
- Paul T. Boggs
Organizations
- University of North Carolina at Chapel Hill