Alternative regularizations for Outer-Approximation algorithms for convex MINLP

In this work, we extend the regularization framework from Kronqvist et al. (Math Program 180(1):285–310, 2020) by incorporating several new regularization functions and develop a regularized single-tree search method for solving convex mixed-integer nonlinear programming (MINLP) problems. We propose...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Journal of global optimization Ročník 84; číslo 4; s. 807 - 842
Hlavní autoři:	Bernal, David E., Peng, Zedong, Kronqvist, Jan, Grossmann, Ignacio E.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Ames Research Center Springer 01.12.2022 Springer US Springer Nature B.V
Témata:	Algorithms Approximation Approximation algorithms Branch and bound method Branch and bound methods Computer Programming And Software Computer Science Convex MINLP Convex mixed-integer nonlinear programming Integer programming Mathematical analysis Mathematics Mathematics and Statistics Mixed integer Mixed integer non-linear programming problems Mixed integer optimization Mixed-integer nonlinear programming Nonlinear programming Open source software Operations Research/Decision Theory Optimization Outer approximation Outer approximation algorithm Outer approximation methods Real Functions Regularisation Regularization Regularization for mixed-integer optimization Regularization function Trees (mathematics) Outer Approximation Convex Mixed-Integer Nonlinear Programming Regularization Mixed-Integer Optimization Regularization for mixed-integer optimization Outer-Approximation Convex MINLP
ISSN:	0925-5001, 1573-2916, 1573-2916
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!