New Underestimator for Univariate Global Optimization
Autor: | Hoai An Le Thi, Ahmed Zidna, Mohand Ouanes |
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Přispěvatelé: | Département de Mathématiques, Faculté des Sciences, Université Mouloud Mammeri de Tizi-Ouzou, Algérie, Laboratoire de Génie Informatique, de Production et de Maintenance (LGIPM), Université de Lorraine (UL) |
Jazyk: | angličtina |
Rok vydání: | 2015 |
Předmět: |
0209 industrial biotechnology
Mathematical optimization 021103 operations research Branch and bound Computer science Efficient algorithm MathematicsofComputing_NUMERICALANALYSIS 0211 other engineering and technologies Regular polygon Univariate 02 engineering and technology 020901 industrial engineering & automation Quadratic equation Convergence (routing) [INFO]Computer Science [cs] Global optimization Global optimization problem ComputingMilieux_MISCELLANEOUS ComputingMethodologies_COMPUTERGRAPHICS |
Zdroj: | Modelling, Computation and Optimization in Information Systems and Management Sciences. Advances in Intelligent Systems and Computing, vol 359. Springer, Cham. Modelling, Computation and Optimization in Information Systems and Management Sciences. Advances in Intelligent Systems and Computing, vol 359. Springer, Cham., pp.403-410, 2015, ⟨10.1007/978-3-319-18161-5_34⟩ Advances in Intelligent Systems and Computing ISBN: 9783319181608 MCO (1) |
Popis: | The aim of this paper is to propose a new underestimator for solving univariate global optimization problems, which is better than the underestimator used in the classical αBB method [1], and the quadratic underestimator developed in [4]. We can propose an efficient algorithm based on Branch and Bound techniques and an efficient w-subdivision for branching. A convex/concave test is added to accelerate the convergence of the algorithm. |
Databáze: | OpenAIRE |
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