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We present a novel analysis of semidefinite programs (SDPs) with positive duality gaps, i.e. different optimal values in the primal and dual problems. These SDPs are extremely pathological, often unsolvable, and also serve as models of more…

Optimization and Control · Mathematics 2020-05-18 Gabor Pataki

We study problems arising in real-time auction markets, common in e-commerce and computational advertising, where bidders face the problem of calculating optimal bids. We focus upon a contract management problem where a demand aggregator is…

Computational Engineering, Finance, and Science · Computer Science 2022-06-28 Ryan J. Kinnear , Ravi R. Mazumdar , Peter Marbach

We study a special class of non-convex quadratic programs subject to two (possibly indefinite) quadratic constraints when the level sets of the constraint functions are {\it not} arranged {\it alternatively.} It is shown in the paper that…

Optimization and Control · Mathematics 2020-12-21 Huu-Quang Nguyen , Ruey-Lin Sheu

Advances in computational optimization allow for the organization of large combinatorial markets. We aim for allocations and competitive equilibrium prices, i.e. outcomes that are in the core. The research is motivated by the design of…

Computer Science and Game Theory · Computer Science 2018-07-24 Martin Bichler , Stefan Waldherr

In many multiagent environments, a designer has some, but limited control over the game being played. In this paper, we formalize this by considering incompletely specified games, in which some entries of the payoff matrices can be chosen…

Computer Science and Game Theory · Computer Science 2021-04-30 Markus Brill , Rupert Freeman , Vincent Conitzer

We provide three new proofs of the strong concavity of the dual function of some convex optimization problems. For problems with nonlinear constraints, we show that the the assumption of strong convexity of the objective cannot be weakened…

Optimization and Control · Mathematics 2021-05-04 Vincent Guigues

Both bilevel and robust optimization are established fields of mathematical optimization and operations research. However, only until recently, the similarities in their mathematical structure has neither been studied theoretically nor…

Optimization and Control · Mathematics 2026-02-20 Henri Lefebvre , Martin Schmidt , Simon Stevens , Johannes Thürauf

In this paper we consider resource allocation problem stated as a convex minimization problem with linear constraints. To solve this problem, we use gradient and accelerated gradient descent applied to the dual problem and prove the…

Optimization and Control · Mathematics 2019-10-01 Anastasiya Ivanova , Pavel Dvurechensky , Alexander Gasnikov , Dmitry Kamzolov

We extend variational quantum optimization algorithms for Quadratic Unconstrained Binary Optimization problems to the class of Mixed Binary Optimization problems. This allows us to combine binary decision variables with continuous decision…

Quantum Physics · Physics 2021-09-13 Lee Braine , Daniel J. Egger , Jennifer Glick , Stefan Woerner

In this paper, we study a constrained utility maximization problem following the convex duality approach. After formulating the primal and dual problems, we construct the necessary and sufficient conditions for both the primal and dual…

Mathematical Finance · Quantitative Finance 2016-12-15 Yusong Li , Harry Zheng

Discretely-constrained Nash-Cournot games have attracted attention as they arise in various competitive energy production settings in which players must make one or more discrete decisions. Gabriel et al. ["Solving discretely-constrained…

Theoretical Economics · Economics 2022-11-24 Dimitri J. Papageorgiou , Francisco Trespalacios , Stuart Harwood

A popular approach in combinatorial optimization is to model problems as integer linear programs. Ideally, the relaxed linear program would have only integer solutions, which happens for instance when the constraint matrix is totally…

Data Structures and Algorithms · Computer Science 2009-09-29 Christoph Durr , Mathilde Hurand

It is well-known that by adding integrality constraints to the semidefinite programming (SDP) relaxation of the max-cut problem, the resulting integer semidefinite program is an exact formulation of the problem. In this paper we show…

Optimization and Control · Mathematics 2023-11-09 Frank de Meijer , Renata Sotirov

Unlike Poker where the action space $\mathcal{A}$ is discrete, differential games in the physical world often have continuous action spaces not amenable to discrete abstraction, rendering no-regret algorithms with…

Computer Science and Game Theory · Computer Science 2025-02-17 Mukesh Ghimire , Zhe Xu , Yi Ren

The canonical duality theory has provided with a unified analytic solution to a range of discrete and continuous problems in global optimization, which can transform a nonconvex primal problem to a concave maximization dual problem over a…

Optimization and Control · Mathematics 2012-10-04 Xiaojun Zhou

The main outcomes of the paper are divided into two parts. First, we present a new dual for quadratic programs, in which, the dual variables are affine functions, and we prove strong duality. Since the new dual is intractable, we consider a…

Optimization and Control · Mathematics 2019-01-31 Moslem Zamani

We present a coordinate ascent method for a class of semidefinite programming problems that arise in non-convex quadratic integer optimization. These semidefinite programs are characterized by a small total number of active constraints and…

Optimization and Control · Mathematics 2020-07-13 Christoph Buchheim , Maribel Montenegro , Angelika Wiegele

Differential positivity and K-cooperativity, a special case of differential positivity, extend differential approaches to control to nonlinear systems with multiple equilibria, such as switches or multi-agent consensus. To apply this…

Optimization and Control · Mathematics 2020-05-12 Dimitris Kousoulidis , Fulvio Forni

In this paper we study two-player bilinear zero-sum games with constrained strategy spaces. An instance of natural occurrences of such constraints is when mixed strategies are used, which correspond to a probability simplex constraint. We…

Computer Science and Game Theory · Computer Science 2022-06-10 Andre Wibisono , Molei Tao , Georgios Piliouras

This article studies convex duality in stochastic optimization over finite discrete-time. The first part of the paper gives general conditions that yield explicit expressions for the dual objective in many applications in operations…

Optimization and Control · Mathematics 2015-04-28 Sara Biagini , Teemu Pennanen , Ari-Pekka Perkkiö