1 citations · 1 across the 5 of their papers we have counts for
6 papers
Relaxations and Duality for Multiobjective Integer Programming
Alex Dunbar, Saumya Sinha, Andrew J Schaefer
Multiobjective integer programs (MOIPs) simultaneously optimize multiple objective functions over a set of linear constraints and integer variables. In this paper, we present conti…
Markov Decision Process Design: A Framework for Integrating Strategic and Operational Decisions
Seth Brown, Saumya Sinha, Andrew J Schaefer
We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates design and operational phases, which are…
On strong duality, theorems of the alternative, and projections in conic optimization
Temitayo Ajayi, Akshay Gupte, Amin Khademi +1
A conic program is the problem of optimizing a linear function over a closed convex cone intersected with an affine preimage of another cone. We analyse three constraint qualificat…
A Gilmore-Gomory-Type Construction of Integer Programming Value Functions
Seth Brown, Wenxin Zhang, Temitayo Ajayi +1
In this paper, we analyze how sequentially introducing decision variables into an integer program (IP) affects the value function and its level sets. We use a Gilmore-Gomory approa…
Theorems of the Alternative for Conic Integer Programming
Temitayo Ajayi, Varun Suriyanarayana, Andrew J. Schaefer
Farkas' Lemma is a foundational result in linear programming, with implications in duality, optimality conditions, and stochastic and bilevel programming. Its generalizations are k…
Approximate Submodularity and Its Implications in Discrete Optimization
Temitayo Ajayi, Taewoo Lee, Andrew Schaefer
Submodularity is a key property in discrete optimization. Submodularity has been widely used for analyzing the greedy algorithm to give performance bounds and providing insight int…