Sequential Convex Programming Methods for Solving Nonlinear Optimization\n Problems with DC constraints

2011/07/28 by Tran Dinh Quoc, Moritz Diehl, Quoc, Tran Dinh +1 · 1 citation
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Optimization and Search Problems #Optimization and Variational Analysis #Sparse and Compressive Sensing Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1107.5841

openalex publication_date 2011/07/28 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28

Abstract

This paper investigates the relation between sequential convex programming\n(SCP) as, e.g., defined in [24] and DC (difference of two convex functions)\nprogramming. We first present an SCP algorithm for solving nonlinear\noptimization problems with DC constraints and prove its convergence. Then we\ncombine the proposed algorithm with a relaxation technique to handle\ninconsistent linearizations. Numerical tests are performed to investigate the\nbehaviour of the class of algorithms.\n

Citations

• Numerical optimization

Cited by

• Parallel and Distributed Methods for Nonconvex Optimization-Part I: Theory

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