Comparative study of RPSALG algorithm for convex semi-infinite programming

A. Auslender (), A. Ferrer (), M. Goberna () and M. López ()

Computational Optimization and Applications, 2015, vol. 60, issue 1, 59-87

Abstract: The Remez penalty and smoothing algorithm (RPSALG) is a unified framework for penalty and smoothing methods for solving min-max convex semi-infinite programing problems, whose convergence was analyzed in a previous paper of three of the authors. In this paper we consider a partial implementation of RPSALG for solving ordinary convex semi-infinite programming problems. Each iteration of RPSALG involves two types of auxiliary optimization problems: the first one consists of obtaining an approximate solution of some discretized convex problem, while the second one requires to solve a non-convex optimization problem involving the parametric constraints as objective function with the parameter as variable. In this paper we tackle the latter problem with a variant of the cutting angle method called ECAM, a global optimization procedure for solving Lipschitz programming problems. We implement different variants of RPSALG which are compared with the unique publicly available SIP solver, NSIPS, on a battery of test problems. Copyright Springer Science+Business Media New York 2015

Keywords: Convex semi-infinite programming; Remez-type methods; Penalty methods; Smoothing methods; Cutting angle method (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10589-014-9667-7

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