We consider a single machine scheduling problem to minimize the completion time variance. This roblem is known to be NP-hard. We prove that if $p_{n-1} = p_{n-2$, then there is an optimal solution of the form $(n,n-2,n-3,…,n-4,n-1)$. A new lower bound are proposed for solving the problem. The test on more than 4000 instances shows … Read more
This work proposes a progressive manifold identification approach for distributed optimization with sound theoretical justifications to greatly reduce both the rounds of communication and the bytes communicated per round for partly-smooth regularized problems such as the $\ell_1$- and group-LASSO-regularized ones. Our two-stage method first uses an inexact proximal quasi-Newton method to iteratively identify a sequence … Read more
We consider a general multi-period repositioning problem in vehicle-sharing networks such as bicycle-sharing systems, free-float car-sharing systems, and autonomous mobility-on-demand systems. This problem is subject to uncertainties along multiple dimensions – including demand, travel time, and repositioning duration – and faces several operational constraints such as the service level and cost budget. We propose a … Read more
The field of Statistical Disclosure Control aims at reducing the risk of re-identification of an individual when disseminating data, and it is one of the main concerns of national statistical agencies. Operations Research (OR) techniques were widely used in the past for the protection of tabular data, but not for microdata (i.e., files of individuals … Read more
We consider the task of proving integer infeasibility of a bounded convex set K in R^n using a general branching proof system. In a general branching proof, one constructs a branching tree by adding an integer disjunction at each node, such that the leaves of the tree correspond to empty sets (i.e., K together with … Read more
We consider a two player zero-sum game with stochastic linear constraints. The probability distributions of the vectors associated with the constraints are partially known. The available information with respect to the distribution is based mainly on the two first moments. In this vein, we formulate the stochastic linear constraints as distributionally robust chance constraints. We … Read more
We consider an n-player non-cooperative game where each player has expected value payoff function and her strategy set is defined by a joint chance constraint. The random constraint vectors are independent. We propose a subset of probability distributions from elliptical family of distributions. We consider the case when the probability distribution of each random constraint … Read more
Linear bilevel optimization problems are often tackled by replacing the linear lower-level problem with its Karush–Kuhn–Tucker (KKT) conditions. The resulting single-level problem can be solved in a branch-and-bound fashion by branching on the complementarity constraints of the lower-level problem’s optimality conditions. While in mixed-integer single-level optimization branch- and-cut has proven to be a powerful extension … Read more
Aggregation of heating, ventilation, and air conditioning (HVAC) loads can provide reserves to absorb volatile renewable energy, especially solar photo-voltaic (PV) generation. However, the time-varying PV generation is not perfectly known when the system operator decides the HVAC control schedules. To consider the unknown uncertain PV generation, in this paper, we formulate a distributionally robust … Read more
The problem of community detection with two equal-sized communities is closely related to the minimum graph bisection problem over certain random graph models. In the stochastic block model distribution over networks with community structure, a well-known semidefinite programming (SDP) relaxation of the minimum bisection problem recovers the underlying communities whenever possible. Motivated by their superior … Read more