An augmented filled function for global nonlinear integer optimization

Juan Di Mauro () and Hugo D. Scolnik ()
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Juan Di Mauro: CONICET-Universidad de Buenos Aires
Hugo D. Scolnik: Universidad de Buenos Aires

TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, 2020, vol. 28, issue 3, No 8, 689-704

Abstract: Abstract The problem of finding global minima of nonlinear discrete functions arises in many fields of practical matters. In recent years, methods based on discrete filled functions have become popular as ways of solving these sort of problems. However, they rely on the steepest descent method for local searches. Here, we present an approach that does not depend on a particular local optimization method, and a new discrete filled function with the useful property that a good continuous global optimization algorithm applied to it leads to an approximation of the solution of the nonlinear discrete problem (Theorem 4). Numerical results are given showing the efficiency of the new approach.

Keywords: Discrete global optimization; Discrete filled function; Nonlinear optimization; Approximate algorithms.; 90-08 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11750-020-00555-0

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