Please use this identifier to cite or link to this item: https://rfos.fon.bg.ac.rs/handle/123456789/3195
Title: Lua APIs for mathematical optimization
Authors: Stanojević, Milan 
Stanojević, Bogdana 
Keywords: Dynamic callable library;AMPL/GMPL languages;CBC solver;ALGENCAN;mathematical optimization
Issue Date: 2024
Publisher: Elsevier
Abstract: In this paper we present our Lua programming language libraries that enable modeling and solving mixed integer linear and nonlinear mathematical optimization problems. On one side, these libraries provide a framework for developing algorithms written in Lua that use certain well known solvers within more complex procedures. On the other side, they facilitate the transformation of both input and output data of a mathematical programming problem, in order to compute the standardized coefficients that have to be transmitted to the solvers or prepare solution of solved problems for further data processing. Both of these use cases, together with Lua programming language simplicity, versatility and performance, make Lua a suitable programming language for use in scientific and engineering researches.
URI: https://rfos.fon.bg.ac.rs/handle/123456789/3195
Appears in Collections:Radovi istraživača / Researchers’ publications

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