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Construction of global optimization constrained NLP test cases from unconstrained problems

Chan, MSC, del Rio-Chanona, EA, Fiorelli, F, Arellano-Garcia, H and Vassiliadis, VS (2016) Construction of global optimization constrained NLP test cases from unconstrained problems Chemical Engineering Research and Design, 109 (May 20). pp. 753-769.

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This paper presents a novel construction technique for constrained nonconvex Nonlinear Programming Problem (NLP) test cases, derived from the evaluation tree structure of standardized bound constrained problems for which the global solution is known. It is demonstrated in a step-by-step procedure how first an equality constrained problem can be derived from an unconstrained one, with bounds imposed on all variables, using the Directed Acyclic Graph (DAG) of the unconstrained objective function and the use of interval arithmetic to derive bounds for the new variables introduced. An advantage of the proposed methodology is that several standard unconstrained global optimization test cases can be constructed for varying number of optimization variables, thus leading to adjustable size derived NLP's. Further to this in a second step it is demonstrated how any subset of the equalities derived can be relaxed into inequalities giving an equivalent optimization problem. Finally, in a third step it is demonstrated how, by reducing the number of equality constraints derived, it is possible to obtain more complex expressions in the constraints and objective function. The methodology is highlighted throughout by motivating examples and a sample code in Mathematica™ is provided in the Appendix.

Item Type: Article
Subjects : Chemical Engineering
Divisions : Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :
Chan, MSC
del Rio-Chanona, EA
Fiorelli, F
Arellano-Garcia, H
Vassiliadis, VS
Date : 2 May 2016
DOI : 10.1016/j.cherd.2016.03.015
Copyright Disclaimer : © 2016 Elsevier Ltd. All rights reserved.
Uncontrolled Keywords : NLP problems, Global optimization, Constrained nonconvex optimization, Unconstrained nonconvex optimization
Depositing User : Symplectic Elements
Date Deposited : 23 Aug 2016 14:58
Last Modified : 31 Oct 2017 18:35

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