The Airlift Planning Problem

The U.S. Transportation Command (USTRANSCOM) is responsible for planning and executing the transportation of U.S. military personnel and cargo by air, land, and sea. The airlift planning problem faced by the air component of USTRANSCOM is to decide how requirements (passengers and cargo) will be assigned to the available aircraft fleet and the sequence of pickups and drop-offs that each aircraft will perform to ensure that the requirements are delivered with minimal delay and with maximum utilization of the available aircraft. This problem is of significant interest to USTRANSCOM because of the highly time-sensitive nature of the requirements that are typically designated for delivery by airlift, as well as the very high cost of airlift operations. At the same time, the airlift planning problem is extremely difficult to solve because of the combinatorial nature of the problem and the numerous constraints present in the problem (such as weight restrictions and crew rest requirements). In this paper, we propose an approach for solving the airlift planning problem faced by USTRANSCOM based on modern, large-scale optimization. Our approach relies on solving a large-scale mixed-integer programming model that disentangles the assignment decision (which aircraft will pickup and deliver which requirement) from the sequencing decision (in what order the aircraft will pickup and deliver its assigned requirements), using a combination of heuristics and column generation. Through computational experiments with both a simulated data set and a planning data set provided by USTRANSCOM, we show that our approach leads to high-quality solutions for realistic instances (e.g., 100 aircraft and 100 requirements) within operationally feasible time frames. Compared with a baseline approach that emulates current practice at USTRANSCOM, our approach leads to reductions in total delay and aircraft time of 8%–12% in simulated data instances and 16%–40% in USTRANSCOM’s planning instances.

Beyond Levels of Automation: Developing More Detailed Guidance for Human Automation Interaction Design

There is growing recognition of a need to go beyond levels of automation frameworks to provide more detailed guidance for design of effective human automation interaction (HAI). Here we present some design questions that are important for designers of HAI to address as they develop the requirements for the software architecture and user interfaces for automated aids. This set of guiding questions has grown out of our experience in developing a series of successful collaborative automation systems for airlift planning and scheduling. We illustrate through examples how answers to these high-level questions helped inform the HAI design decisions we confronted. The set of questions are offered in an attempt to broaden the discussion of how best to provide guidance to system developers confronted with HAI design challenges.