Interval-based Dynamic Discretization Discovery for Solving the Continuous-Time Service Network Design Problem

We introduce an effective and efficient iterative algorithm for solving the Continuous-Time Service Network Design Problem. The algorithm achieves its efficiency by carefully and dynamically refining partially time-expanded network models so that only a small number of small integer programs, defined over these networks, need to be solved. An extensive computational study shows that the … Read more

Data-Driven Maintenance and Operations Scheduling in Power Systems under Decision-Dependent Uncertainty

Generator maintenance scheduling plays a pivotal role in ensuring uncompromising operations of power systems. There exists a tight coupling between the condition of the generators and corresponding operational schedules, significantly affecting reliability of the system. In this study, we effectively model and solve an integrated condition-based maintenance and operations scheduling problem for a fleet of … Read more

Endogenous Price Zones and Investment Incentives in Electricity Markets: An Application of Multilevel Optimization with Graph Partitioning

In the course of the energy transition, load and supply centers are growing apart in electricity markets worldwide, rendering regional price signals even more important to provide adequate locational investment incentives. This paper focuses on electricity markets that operate under a zonal pricing market design. For a fixed number of zones, we endogenously derive the … Read more

Dynamic Courier Routing for a Food Delivery Service

Services like Grubhub and UberEats have revolutionized the way that diners can find and order from restaurants. The standard business model for such services, however, allows diners to order from only one restaurant at a time. Inspired by a food delivery service in the southeastern United States, this paper proposes the framework for a more … Read more

Learning a Mixture of Gaussians via Mixed Integer Optimization

We consider the problem of estimating the parameters of a multivariate Gaussian mixture model (GMM) given access to $n$ samples $\x_1,\x_2,\ldots ,\x_n \in\mathbb{R}^d$ that are believed to have come from a mixture of multiple subpopulations. State-of-the-art algorithms used to recover these parameters use heuristics to either maximize the log-likelihood of the sample or try to … Read more

Delay and disruption management at ATM: technical details

Most of the local public transit companies have vehicle monitoring systems able to collect huge quantities of data in real-time. Typically, these data are used to measure the performance of the transportation system, and rarely they are fully exploited to improve it and to tackle disruptions. In this report we take into consideration the case … Read more

Multi-Stage Stochastic Programming Models for Provisioning Cloud Computing Resources

We focus on the resource provisioning problem of a cloud consumer from an Infrastructure-as-a-Service type of cloud. The cloud provider offers two deployment options, which can be mixed and matched as appropriate. Cloud instances may be reserved for a fixed time period in advance at a smaller usage cost per hour but require a full … Read more

Decision Diagrams for Solving Traveling Salesman Problems with Pickup and Delivery in Real Time

The Traveling Salesman Problem with Pickup and Delivery seeks a minimum cost path with pickups preceding deliveries. It is important in on-demand last-mile logistics, such as ride sharing and meal delivery. We examine the use of low-width Decision Diagrams in a branch-and-bound with and without Assignment Problem inference duals as a primal heuristic for finding … Read more

Robust Optimization of a Broad Class of Heterogeneous Vehicle Routing Problems under Demand Uncertainty

This paper studies robust variants of an extended model of the classical Heterogeneous Vehicle Routing Problem (HVRP), where a mixed fleet of vehicles with different capacities, availabilities, fixed costs and routing costs is used to serve customers with uncertain demand. This model includes, as special cases, all variants of the HVRP studied in the literature … Read more

Analysis of Process Flexibility Designs under Disruptions

Most of the previous studies of process flexibility designs have focused on expected sales and demand uncertainty. In this paper, we examine the worst-case performance of flexibility designs in the case of demand and supply uncertainties, where the latter can be in the form of either plant or arc disruptions. We define the Plant Cover … Read more