Building robust airline scheduling models involves constructing schedules and routes with reduced levels of flight delays as well as fewer passenger and crew disruptions. In this paper, we study different classes of models to achieve robust airline scheduling solutions, with a focus on the...

Optimization under uncertainty has been a well-studied field, with significant interest generated in this field in the past four decades. This paper is both practical and expository - its purpose is to: discuss the process of generating robust solutions, highlight issues that arise in practice,...

Ancillaries in the travel industry are now a major stream for revenue and profitability. Ancillaries are optional products or services whose sales depend on an individual's personal preference and their trip context. Conventional pricing strategies for ancillaries based on poorly optimized or...

Optimization under uncertainty has been a well-studied field, with renewed interest generated in this field in the past four decades. This paper is both practical and expository, its purpose is to: discuss the process of generating robust solutions, highlight issues that arise in practice, and...

Modern shipping ports require computer systems to accommodate an increasing number of port calls, larger vessel sizes, and tighter supply chains. Disruptions to assets on these networks have the potential to propagate to other critical infrastructures at great economic cost. Such disruptions may...

We present an efficient data-driven computational bounding and solution approach for static allocation of ambulance fleet and its dynamic redeployment, where the goal is to position (or re-position) ambulances to bases to maximize the systems service level. We leverage the framework presented,...

In many emerging economies, callers may abandon ambulance requests due to a combination of operational (small fleet size), infrastructural (long travel times) and behavioral factors (low trust in the ambulance system). As a result, ambulance capacity, which is already scarce, is wasted in...

We present a novel modeling and algorithmic approach, a Maximum Entropy Principle (MEP) heuristic for Routing and Scheduling, for a large class of problems including the Traveling Salesman Problem (TSP), multiple Traveling Salesmen Problem (mTSP), the Vehicle Routing Problem (VRP) and the...

Optimization under uncertainty has been a well-studied field, with significant interest generated in this field in the past four decades. This paper is both practical and expository - its purpose is to: discuss the process of generating robust solutions, highlight issues that arise in practice,...