Partial spectral projected gradient method with active-set strategy for linearly constrained optimization

A method for linearly constrained optimization which modifies and generalizes recent box-constraint optimization algorithms is introduced. The new algorithm is based on a relaxed form of Spectral Projected Gradient iterations. Intercalated with these projected steps, internal iterations restricted to faces of the polytope are performed, which enhance the efficiency of the algorithms. Convergence proofs are given and numerical experiments are included and commented. Software supporting this paper is available through the Tango Project web page: http://www.ime.usp.br/∼egbirgin/tango/. Key words: Linearly constrained optimization, spectral projected gradient method, active set methods.

• Type: Journal
• Year: 2010
• Where: NA
• Authors: Marina Andretta, Ernesto G. Birgin, José Mario Martínez
• Keywords: Algorithms, Gradient Iterations, NA 2010, Tango Project Web