69 citations · 178 across the 26 of their papers we have counts for
28 papers
SDDmiP.jl: A Software Package with a Provably Convergent Benders Algorithm for Multi-Stage Stochastic Mixed-Integer Programming
Akul Bansal, Simge Küçükyavuz
We present an open-source software package that implements a provably convergent Benders-type decomposition algorithm for multistage stochastic integer programs. In addition to sta…
Coordinate Optimality Reformulation for Mixed-Integer Convex Programs with Indicators
Tong Xu, Salar Fattahi, Andrés Gómez +1
We consider mixed-integer convex optimization problems in which binary indicators control continuous variables. We introduce the \emph{Coordinate Optimality Reformulation} (CORe) f…
Normalization of ReLU Dual for Cut Generation in Stochastic Mixed-Integer Programs
Akul Bansal, Simge Küçükyavuz
We study the Rectified Linear Unit (ReLU) dual, an existing dual formulation for stochastic programs that reformulates non-anticipativity constraints using ReLU functions to genera…
An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Models
Tong Xu, Simge Küçükyavuz, Ali Shojaie +1
This paper studies the problem of learning Bayesian networks from continuous observational data, generated according to a linear Gaussian structural equation model. We consider an…
A Parametric Approach for Solving Convex Quadratic Optimization with Indicators Over Trees
Aaresh Bhathena, Salar Fattahi, Andrés Gómez +1
This paper investigates convex quadratic optimization problems involving indicator variables, each associated with a continuous variable, particularly focusing on scenarios whe…
Polyhedral Analysis of Quadratic Optimization Problems with Stieltjes Matrices and Indicators
Peijing Liu, Alper Atamtürk, Andrés Gómez +1
In this paper, we consider convex quadratic optimization problems with indicators on the continuous variables. In particular, we assume that the Hessian of the quadratic term is a…
Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
Tong Xu, Armeen Taeb, Simge Küçükyavuz +1
We study the problem of learning directed acyclic graphs from continuous observational data, generated according to a linear Gaussian structural equation model. State-of-the-art st…
Mixed-Integer Programming for a Class of Robust Submodular Maximization Problems
Hsin-Yi Huang, Hao-Hsiang Wu, Simge Kucukyavuz
We consider robust submodular maximization problems (RSMs), where given a set of monotone submodular objective functions, the robustness is with respect to the worst-case (scal…
On Constrained Mixed-Integer DR-Submodular Minimization
Qimeng Yu, Simge Küçükyavuz
DR-submodular functions encompass a broad class of functions which are generally non-convex and non-concave. We study the problem of minimizing any DR-submodular function, with con…
On the convex hull of convex quadratic optimization problems with indicators
Linchuan Wei, Alper Atamtürk, Andrés Gómez +1
We consider the convex quadratic optimization problem with indicator variables and arbitrary constraints on the indicators. We show that a convex hull description of the associated…
Strong valid inequalities for a class of concave submodular minimization problems under cardinality constraints
Qimeng Yu, Simge Küçükyavuz
We study the polyhedral convex hull structure of a mixed-integer set which arises in a class of cardinality-constrained concave submodular minimization problems. This class of prob…
Chance-Constrained Optimization under Limited Distributional Information: A Review of Reformulations Based on Sampling and Distributional Robustness
Simge Küçükyavuz, Ruiwei Jiang
Chance-constrained programming (CCP) is one of the most difficult classes of optimization problems that has attracted the attention of researchers since the 1950s. In this survey,…
An Exact Cutting Plane Method for -submodular Function Maximization
Qimeng Yu, Simge Küçükyavuz
A natural and important generalization of submodularity -- -submodularity -- applies to set functions with arguments and appears in a broad range of applications, such as in…
Strong Formulations for Distributionally Robust Chance-Constrained Programs with Left-Hand Side Uncertainty under Wasserstein Ambiguity
Nam Ho-Nguyen, Fatma Kılınç-Karzan, Simge Küçükyavuz +1
Distributionally robust chance-constrained programs (DR-CCP) over Wasserstein ambiguity sets exhibit attractive out-of-sample performance and admit big--based mixed-integer prog…
Ideal formulations for constrained convex optimization problems with indicator variables
Linchuan Wei, Andres Gomez, Simge Kucukyavuz
Motivated by modern regression applications, in this paper, we study the convexification of a class of convex optimization problems with indicator variables and combinatorial const…
Consistent Second-Order Conic Integer Programming for Learning Bayesian Networks
Simge Kucukyavuz, Ali Shojaie, Hasan Manzour +2
Bayesian Networks (BNs) represent conditional probability relations among a set of random variables (nodes) in the form of a directed acyclic graph (DAG), and have found diverse ap…
Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty under Wasserstein Ambiguity
Nam Ho-Nguyen, Fatma Kılınç-Karzan, Simge Küçükyavuz +1
We consider exact deterministic mixed-integer programming (MIP) reformulations of distributionally robust chance-constrained programs (DR-CCP) with random right-hand sides over Was…
A Polyhedral Approach to Bisubmodular Function Minimization
Qimeng Yu, Simge Kucukyavuz
We consider minimization problems with bisubmodular objective functions. We propose valid inequalities, namely the poly-bimatroid inequalities, and provide a complete linear descri…
Joint chance-constrained programs and the intersection of mixing sets through a submodularity lens
Fatma Kılınç-Karzan, Simge Küçükyavuz, Dabeen Lee
A particularly important substructure in modeling joint linear chance-constrained programs with random right-hand sides and finite sample space is the intersection of mixing sets w…
Integer Programming for Learning Directed Acyclic Graphs from Continuous Data
Hasan Manzour, Simge Küçükyavuz, Ali Shojaie
Learning directed acyclic graphs (DAGs) from data is a challenging task both in theory and in practice, because the number of possible DAGs scales superexponentially with the numbe…
An Exact Method for Constrained Maximization of the Conditional Value-at-Risk of a Class of Stochastic Submodular Functions
Hao-Hsiang Wu, Simge Kucukyavuz
We consider a class of risk-averse submodular maximization problems (RASM) where the objective is the conditional value-at-risk (CVaR) of a random nondecreasing submodular function…
Vector-Valued Multivariate Conditional Value-at-Risk
Merve Merakli, Simge Kucukyavuz
In this study, we propose a new definition of multivariate conditional value-at-risk (MCVaR) as a set of vectors for discrete probability spaces. We explore the properties of the v…
Chance-Constrained Combinatorial Optimization with a Probability Oracle and Its Application to Probabilistic Partial Set Covering
Hao-Hsiang Wu, Simge Kucukyavuz
We investigate a class of chance-constrained combinatorial optimization problems. Given a pre-specified risk level , the chance-constrained program aims to find the min…
Path Cover and Path Pack Inequalities for the Capacitated Fixed-Charge Network Flow Problem
Alper Atamturk, Birce Tezel, Simge Kucukyavuz
Capacitated fixed-charge network flows are used to model a variety of problems in telecommunication, facility location, production planning and supply chain management. In this pap…