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Bounded lower subdifferentiability optimization techniques: applications

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Abstract

In this article we develop a global optimization algorithm for quasiconvex programming where the objective function is a Lipschitz function which may have “flat parts”. We adapt the Extended Cutting Angle method to quasiconvex functions, which reduces significantly the number of iterations and objective function evaluations, and consequently the total computing time. Applications of such an algorithm to mathematical programming problems in which the objective function is derived from economic systems and location problems are described. Computational results are presented.

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Authors and Affiliations

  1. School of Information Technology, Deakin University, Melbourne, VIC, Australia

    Gleb Beliakov

  2. Departament de Matemàtica Aplicada I, Universitat Politècnica de Catalunya, Barcelona, Spain

    Albert Ferrer

Authors
  1. Gleb Beliakov
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  2. Albert Ferrer
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Correspondence to Gleb Beliakov.

Additional information

The research of Albert Ferrer has been partially supported by the Ministerio de Ciencia y Tecnología, Project MCYT, DPI 2005-09117-C02-01.

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Beliakov, G., Ferrer, A. Bounded lower subdifferentiability optimization techniques: applications. J Glob Optim 47, 211–231 (2010). https://doi.org/10.1007/s10898-009-9467-2

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  • DOI: https://doi.org/10.1007/s10898-009-9467-2

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