In this work, we study the problem of scheduling courses and instructors in the Mathematics Department at the United States Naval Academy (USNA) in a resilient manner. Every semester, the department needs to schedule around 70 instructors and 150-180 course sections into 30 class periods and 30 rooms. We formulate a stochastic integer linear program … Read more
Despite recent interest in multiobjective integer programming, few algorithms exist for solving biobjective mixed integer programs. We present such an algorithm: the Boxed Line Method. For one of its variants, we prove that the number of single-objective integer programs solved is bounded by a linear function of the number of nondominated line segments in the … Read more
The assortment of products carried by a store has a crucial impact on its success. However, finding the right mix of products to attract a large portion of the customers is a challenging task. Several mathematical models have been proposed to optimize assortments. In particular, rank-based choice models have been acknowledged for representing well high-dimensional … Read more
The bootstrap is a nonparametric approach for calculating quantities, such as confidence intervals, directly from data. Since calculating exact bootstrap quantities is believed to be intractable, randomized resampling algorithms are traditionally used. Motivated by the fact that the variability from randomization can lead to inaccurate outputs, we propose a deterministic approach. First, we establish several … Read more
Unmanned Aerial Vehicles (UAVs), commonly referred to as drones, have recently seen an increased level of interest as their potential use in same-day home delivery has been promoted and advocated by large retailers and courier delivery companies. We introduce a novel way to exploit drones in same-day home delivery settings: drone resupply. We consider a … Read more
The current best exact algorithms for the Capacitated Arc Routing Problem are based on the combination of cut and column generation. This work presents a deep theoretical investigation of the formulations behind those algorithms, classifying them and pointing similarities and differences, advantages and disadvantages. In particular, we discuss which families of cuts and branching strategies … Read more
We introduce a new generalization of the classical planar maximum coverage location problem (PMCLP) in which demand zones and service zone of each facility are represented by spatial objects such as circles, polygons, etc., and are allowed to be located anywhere in a continuous plane. In addition, we allow partial coverage in its true sense, … Read more
This paper jointly addresses two major challenges in power system operations: i) dealing with non-convexity in the power flow equations, and ii) systematically capturing uncertainty in renewable power availability and in active and reactive power consumption at load buses. To overcome these challenges, this paper proposes a two-stage adaptive robust optimization model for the multi-period … Read more
Given an existing Mobile Edge Cloud (MEC) network including virtualization facilities of limited capacity, and a set of mobile Access Points (AP) whose data traffic demand changes over time, we aim at finding plans for assigning APs traffic to MEC facilities so that the demand of each AP is satisfied and MEC facility capacities are … Read more
There is an undeniable global shortage of skillful nurses. This is a problem of high priority, which is correlated to workforce management issues. These issues can be palliated by increasing nurses’ satisfaction based on flexible rosters using automated nurse rostering. This paper in concerned with nurse rostering based on constraint programming by satisfying global constraints, … Read more