The Sequential Unconstrained Minimization Technique for Nonlinear Programing, a Primal-Dual Method

This article is based on an idea proposed by C. W. Carroll for transforming a mathematical programming problem into a sequence of unconstrained minimization problems. It describes the theoretical validation of Carroll's proposal for the convex programming problem. A number of important new results are derived that were not originally envisaged: The method generates primal-feasible and dual-feasible points, the primal objective is monotonically decreased, and a subproblem of the original programming problem is solved with each unconstrained minimization. Briefly surveyed is computational experience with a newly developed algorithm that makes the technique competitive with known methodology. (A subsequent article describing the computational algorithm is in preparation.)

• 저널Management Science · 10(2) · 360–366
• 토픽Advanced Optimization Algorithms Research · Numerical Analysis
• DOI10.1287/mnsc.10.2.360
• 저자Anthony V. Fiacco, Garth P. McCormick