Optimization via Relaxation and Decomposition : Applications to Large-Scale Engineering Problems

by Gonzalo E. Constante-Flores, Antonio J. Conejo

Relaxation and Decomposition -- Simplifying via Reformulation, Approximation, and Relaxation -- Approximating and Relaxing Optimization Problems -- Learning-Assisted Relaxations and Approximations -- Solving Optimization Problems with Complicating Variables -- Solving Optimization Problems via Lagrangian Decomposition -- Relaxations and Decomposition in Power Systems Operations.

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Year of publication:	2025
Authors:	Constante-Flores, Gonzalo E. ; Conejo, Antonio J.
Publisher:	2025.: Cham : Springer Nature Switzerland 2025.: Cham : Imprint: Springer
Subject:	Linear and nonlinear relaxations and approximations \| Nonlinear optimization \| Linear optimization \| Complicating constraints \| Complicating variables decomposition techniques \| Engineering applications \| Large-scale optimization problems \| Reformulation \| Approximating optimization problems \| Linearization \| Convexification \| Solution initialization \| Constraint simplification \| Variable reduction \| Machine learning for optimization \| Complicating variables \| Benders' decomposition \| Lagrangian relaxation \| Energy, power, and chemical engineering \| Mathematische Optimierung \| Mathematical programming \| Theorie \| Theory \| Dekompositionsverfahren \| Decomposition method \| Künstliche Intelligenz \| Artificial intelligence

Extent:	1 Online-Ressource (XVII, 262 p. 56 illus., 36 illus. in color.)
Series:	International Series in Operations Research & Management Science ; 364
Type of publication:	Book / Working Paper
Language:	English
ISBN:	978-3-031-87405-5 ; 978-3-031-87404-8 ; 978-3-031-87406-2 ; 978-3-031-87407-9
Other identifiers:	10.1007/978-3-031-87405-5 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10015406992