A Unified Framework for Multistage and Multilevel Mixed Integer Linear Optimization

We introduce a unified framework for the study of multilevel mixed integer linear optimization problems and multistage stochastic mixed integer linear optimization problems with recourse. The framework highlights the common mathematical structure of the two problems and allows for the development of a common algorithmic framework. Focusing on the two-stage case, we investigate, in particular, … Read more

A Framework for Generalized Benders’ Decomposition and Its Application to Multilevel Optimization

We describe an algorithmic framework generalizing the well-known framework originally introduced by Benders. We apply this framework to several classes of optimization problems that fall under the broad umbrella of multilevel/multistage mixed integer linear optimization problems. The development of the abstract framework and its application to this broad class of problems provides new insights and … Read more

The Magic of Nash Social Welfare in Optimization: Do Not Sum, Just Multiply!

In this paper, we explain some key challenges when dealing with a single/multi-objective optimization problem in practice. To overcome these challenges, we present a mathematical program that optimizes a Nash Social Welfare function. We refer to this mathematical program as the Nash Social Welfare Program (NSWP). An interesting property of the NSWP is that it … Read more

The Value of Randomized Strategies in Distributionally Robust Risk Averse Network Interdiction Games

Conditional Value at Risk (CVaR) is widely used to account for the preferences of a risk-averse agent in the extreme loss scenarios. To study the effectiveness of randomization in interdiction games with an interdictor that is both risk and ambiguity averse, we introduce a distributionally robust network interdiction game where the interdictor randomizes over the … Read more

Computing mixed strategies equilibria in presence of switching costs by the solution of nonconvex QP problems

In this paper we address a game theory problem arising in the context of network security. In traditional game theory problems, given a defender and an attacker, one searches for mixed strategies which minimize a linear payoff functional. In the problem addressed in this paper an additional quadratic term is added to the minimization problem. … Read more

Risk-Averse Bargaining in a Stochastic Optimization Context

Problem definition: Bargaining situations are ubiquitous in economics and management. We consider the problem of bargaining for a fair ex-ante distribution of random profits arising from a cooperative effort of a fixed set of risk-averse agents. Our approach integrates optimal managerial decision making into bargaining situations with random outcomes and explicitly models the impact of … Read more

Games with distributionally robust joint chance constraints

This paper studies an n-player non-cooperative game with strategy sets defined by stochastic linear constraints. The stochastic constraints of each player are jointly satisfied with a probability exceeding a given threshold. We consider the case where the row vectors defining the constraints are independent random vectors whose probability distributions are not completely known and belong … Read more

Gaddum’s test for symmetric cones

A real symmetric matrix “A” is copositive if the inner product if Ax and x is nonnegative for all x in the nonnegative orthant. Copositive programming has attracted a lot of attention since Burer showed that hard nonconvex problems can be formulated as completely-positive programs. Alas, the power of copositive programming is offset by its … Read more

Optimal time-and-level-of-use price setting for an energy retailer

This paper presents a novel price setting optimization problem for an energy retailer in the smart grid. In this framework the retailer buys energy from multiple generators via bilateral contracts, and sells it to a population of smart homes using Time-and-Level-of-Use prices (TLOU). TLOU is an energy price structure recently introduced in the literature, where … Read more

Exact Solution Approaches for Integer Linear Generalized Maximum Multiplicative Programs Through the Lens of Multi-objective Optimization

We study a class of single-objective nonlinear optimization problems, the so-called Integer Linear Generalized Maximum Multiplicative Programs (IL-GMMP). This class of optimization problems has a significant number of applications in different fields of study including but not limited to game theory, systems reliability, and conservative planning. An IL-GMMP can be reformulated as a mixed integer … Read more