New Classes of Globally Convexized Filled Functions for Global Optimization

Stefano Lucidi (lucididis.uniroma1.it)
Veronica Piccialli (picciallidis.uniroma1.it)

Abstract: We propose new classes of globally convexized filled functions. Unlike the globally convexized filled functions previously proposed in literature, the ones proposed in this paper are continuously differentiable and, under suitable assumptions, their unconstrained minimization allows to escape from any local minima of the original objective function. Moreover we show that the properties of the proposed functions can be extended to the case of box constrained minimization problems. We also report the results of a preliminary numerical experience.

Keywords: Filled functions, Global Optimization, Nonlinear Optimization

Category 1: Global Optimization (Theory )

Category 2: Nonlinear Optimization

Citation: Technical Report 15-01 Dipartimento di Informatica e Sistemistica, Università degli Studi di Roma La Sapienza june 2001 to appear on Journal of Global Optimization

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Entry Submitted: 10/10/2001
Entry Accepted: 10/12/2001
Entry Last Modified: 05/03/2002

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