Results 1 to 10 of about 336,678 (210)
Sparse Poisson regression via mixed-integer optimization. [PDF]
PLoS ONE, 2021 We present a mixed-integer optimization (MIO) approach to sparse Poisson regression. The MIO approach to sparse linear regression was first proposed in the 1970s, but has recently received renewed attention due to advances in optimization algorithms and ...
Hiroki Saishu, Kota Kudo, Yuichi Takano
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Mixed-Integer Optimization with Constraint Learning [PDF]
Operations Research, 2021 In today’s data-driven world, there is a growing opportunity for optimization models to more closely resemble real-world scenarios, namely through learning constraints or objective functions that are not explicitly known and must be estimated through ...
Donato Maragno +5 more
semanticscholar +3 more sources
Online Mixed-Integer Optimization in Milliseconds [PDF]
INFORMS Journal on Computing, 2019 We propose a method to approximate the solution of online mixed-integer optimization (MIO) problems at very high speed using machine learning. By exploiting the repetitive nature of online optimization, we can greatly speed up the solution time.
D. Bertsimas, Bartolomeo Stellato
semanticscholar +3 more sources
A Survey on Mixed-Integer Programming Techniques in Bilevel Optimization
EURO Journal on Computational Optimization, 2021 Bilevel optimization is a field of mathematical programming in which some variables are constrained to be the solution of another optimization problem. As a consequence, bilevel optimization is able to model hierarchical decision processes.
Thomas Kleinert +3 more
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Integer convex minimization by mixed integer linear optimization [PDF]
Operations Research Letters, 2014 Minimizing a convex function over the integral points of a bounded convex set is polynomial in fixed dimension (Grötschel et al., 1988). We provide an alternative, short, and geometrically motivated proof of this result.
Oertel, Timm +2 more
core +3 more sources
Online Superstructure Optimization for Energy Saving of an Industrial Gas Distribution System [PDF]
Chemical Engineering Transactions, 2012 Mixed-integer optimization is a common approach to handle decision-making problems. Nevertheless, such an approach still presents certain operational limitations, especially for online superstructures.
M. D‘Isanto +4 more
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Optimal Biocompatible Solvent Design by Mixed-integer Hybrid Differential Evolution [PDF]
Bioautomation, 2008 In this study, a flexible optimization approach is introduced to design an optimal biocompatible solvent for an extractive fermentation process with cell-recycling.
Hou-Chieh Cheng, Feng-Sheng Wang
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Implied Integrality in Mixed-Integer Optimization
Conference on Integer Programming and Combinatorial OptimizationImplied-integer detection is a well-known presolving technique that is used by many Mixed-Integer Linear Programming solvers. Informally, a variable is said to be implied integer if its integrality is enforced implicitly by integrality of other variables
R. V. D. Hulst, Matthias Walter
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Learning sparse nonlinear dynamics via mixed-integer optimization [PDF]
Nonlinear dynamics, 2022 Discovering governing equations of complex dynamical systems directly from data is a central problem in scientific machine learning. In recent years, the sparse identification of nonlinear dynamics (SINDy) framework, powered by heuristic sparse ...
D. Bertsimas, Wes Gurnee
semanticscholar +1 more source
Applications of Stochastic Mixed-Integer Second-Order Cone Optimization
IEEE Access, 2022 Second-order cone programming problems are a tractable subclass of convex optimization problems that can be solved using polynomial algorithms. In the last decade, stochastic second-order cone programming problems have been studied, and efficient ...
Baha Alzalg, Hadjer Alioui
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