A Decomposition Heuristic for Mixed-Integer Supply Chain Problems

Mixed-integer supply chain models typically are very large but are also very sparse and can be decomposed into loosely coupled blocks. In this paper, we use general-purpose techniques to obtain a block decomposition of supply chain instances and apply a tailored penalty alternating direction method, which exploits the structural properties of the decomposed instances. We … Read more

A Robust Optimization Approach for the Unrelated Parallel Machine Scheduling Problem

In this paper, we address the Unrelated Parallel Machine Scheduling Problem (UPMSP) with sequence- and machine-dependent setup times and job due-date constraints. Different uncertainties are typically involved in real-world production planning and scheduling problems. If ignored, they can lead to suboptimal or even infeasible schedules. To avoid this, we present two new robust optimization models … Read more

Vehicle Routing Problem with Steep Roads

Most routing decisions assume that the world is flat meaning that routing costs are modelled as a weighted sum of total distance and time spend by delivery vehicles. However, this assumption does not apply for urban logistics operations in cities with significant altitude differences. We fill a space in the VRP literature and model routing … Read more

Snow Plow Route Optimization: A Constraint Programming Approach

Many cities have to cope with annual snowfall, but are struggling to manage their snow plowing activities efficiently. Despite the fact that winter road maintenance has been the subject of many research papers over the last 3 decades, very few practical decision support systems have been developed to deal with the complex decision problems involved … Read more

Dynamic optimization for airline maintenance operations

The occurrence of unexpected aircraft maintenance tasks can produce expensive changes in an airline’s operation. When it comes to critical tasks, it might even cancel programmed flights. Despite of it, the challenge of scheduling aircraft maintenance operations under uncertainty has received limited attention in the scientific literature. We study a dynamic airline maintenance scheduling problem, … Read more

The Value of Limited Flexibility in Service Network Designs

Less-than-truckload carriers rely on the consolidation of freight from multiple shippers to achieve economies of scale. Collected freight is routed through a number of transfer terminals at each of which shipments are grouped together for the next leg of their journeys. We study the service network design problem confronted by these carriers. This problem includes … Read more

A Framework for Peak Shaving Through the Coordination of Smart Homes

In demand–response programs, aggregators balance the needs of generation companies and end-users. This work proposes a two-phase framework that shaves the aggregated peak loads while maintaining the desired comfort level for users. In the first phase, the users determine their planned consumption. For the second phase, we develop a bilevel model with mixed-integer variables and … Read more

Risk Aversion to Parameter Uncertainty in Markov Decision Processes with an Application to Slow-Onset Disaster Relief

In classical Markov Decision Processes (MDPs), action costs and transition probabilities are assumed to be known, although an accurate estimation of these parameters is often not possible in practice. This study addresses MDPs under cost and transition probability uncertainty and aims to provide a mathematical framework to obtain policies minimizing the risk of high long-term … Read more

Optimizing the Recovery of Disrupted Multi-Echelon Assembly Supply Chain Networks

We consider optimization problems related to the scheduling of multi-echelon assembly supply chain (MEASC) networks that have applications in the recovery from large-scale disruptive events. Each manufacturer within this network assembles a component from a series of sub-components received from other manufacturers. We develop scheduling decision rules that are applied locally at each manufacturer and … Read more

Dynamic Discretization Discovery Algorithms for Time-Dependent Shortest Path Problems

Finding a shortest path in a network is an iconic optimization problem. We focus on settings in which the travel time on an arc in the network depends on the time at which traversal of the arc begins. In such settings, reaching the sink as early as possible is not the only objective of interest. … Read more