Combining Cross-Entropy and MADS Methods for Inequality Constrained Global Optimization
| Autor: | Romain Couderc, Jean Bigeon, Charles Audet |
|---|---|
| Přispěvatelé: | Groupe d’études et de recherche en analyse des décisions (GERAD), Université du Québec à Montréal = University of Québec in Montréal (UQAM)-HEC Montréal (HEC Montréal)-McGill University = Université McGill [Montréal, Canada]-École Polytechnique de Montréal (EPM), Laboratoire des Sciences du Numérique de Nantes (LS2N), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
021103 operations research Cross Entropy Computer science Feasible region Blackbox optimization [INFO.INFO-CE]Computer Science [cs]/Computational Engineering Finance and Science [cs.CE] 0211 other engineering and technologies Constrained optimization Derivative-free optimization Multivariate normal distribution 010103 numerical & computational mathematics 02 engineering and technology 01 natural sciences Maxima and minima Cross entropy Convergence (routing) MADS Global optimization 0101 mathematics [MATH]Mathematics [math] Heuristics |
| Zdroj: | SN Operations Research Forum SN Operations Research Forum, Springer, 2021, 2 (3), ⟨10.1007/s43069-021-00075-y⟩ |
| ISSN: | 2662-2556 |
| DOI: | 10.1007/s43069-021-00075-y⟩ |
| Popis: | International audience; This paper proposes a way to combine the Mesh Adaptive Direct Search (Mads) algorithm with the Cross-Entropy (CE) method for nonsmooth constrained optimization. The CE method is used as an exploration step by the Mads algorithm. The result of this combination retains the convergence properties of Mads and allows an efficient exploration in order to move away from local minima. The CE method samples trial points according to a multivariate normal distribution whose mean and standard deviation are calculated from the best points found so far. Numerical experiments show the efficiency of this method compared to other global optimization heuristics. Moreover, applied on complex engineering test problems, this method allows an important improvement to reach the feasible region and to escape local minima. |
| Databáze: | OpenAIRE |
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