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Multidimensional Lipschitz global optimization based on efficient diagonal partitions
Authors:Dmitri E. Kvasov
Affiliation:(1) Dipartimento di Statistica, Probabilità e Statistiche Applicate, Università di Roma “La Sapienza”, Rome, Italy;(2) Present address: D.E.I.S., Università della Calabria, Via P. Bucci, Cubo 42C, 87036 Rende (CS), Italy
Abstract:This is a summary of the author’s PhD thesis, supervised by Yaroslav D. Sergeyev and defended on May 5, 2006, at the University of Rome “La Sapienza”. The thesis is written in English and is available from the author upon request. In this work, the global optimization problem of a multidimensional “black-box” function satisfying the Lipschitz condition over a hyperinterval with an unknown Lipschitz constant is considered. The objective function is assumed hard to evaluate. A new efficient diagonal scheme for constructing fast algorithms for solving this problem is examined and illustrated by developing several powerful global optimization methods. A deep theoretical study is performed which highlights the benefit of the approach introduced over traditionally used diagonal algorithms. Theoretical conclusions are confirmed by results of extensive numerical experiments.
Keywords:Global optimization  Black-box functions  Derivative-free methods  Partition strategies  Diagonal approach
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