Applying the Multiple Multidimensional Knapsack Assignment Problem to a Cargo Allocation and Transportation Problem with Stochastic Demand

The US military relies on airlift to not only deploy and sustain U.S. armed forces anywhere in the world but also to rapidly mobilize humanitarian efforts and supplies. Operations already impacted by the limited capacity of aircraft also fall prey to dynamic requirements and differing priorities of multiple global locations. A growing concern for the modern military budget is how to provide airlift functions expediently and economically while mitigating the costs of shortfalls and overages. Utilizing fiscal year 2017-2018 cargo data published by the 618th Air Operations Center and modeling this problem as a multiple multidimensional knapsack assignment problem (MMKAP), this work investigates how categorical assumptions about demand affect aircraft allocation and assesses the economic penalties associated with shorting or exceeding demand in the event of mis-estimation given a stochastic demand. This work starts with the general formulation of a new variant of the MMKAP and applies the MMKAP to a notional military airlift example with two supply, two demand nodes, two item types, and three aircraft types. After a deterministic solution is found, the effects of a stochastic demand are explored using different cost models and random draws from distribution functions based on reported cargo shipment data. This research concludes that there are levels at which demand expectations can be set to mitigate economic penalties given a fixed cost penalty and a variable cost penalty

Optimization Modeling for Airlift Mobility

We describe a multi-period optimization model, implemented in GAMS, to help the U.S. Air Force improve logistical efficiency. It determines the maximum on-time throughput of cargo and passengers that can be transported within a given aircraft fleet over a given network, subject to appropriate physical and policy constraints. The model can be used to help answer questions about selecting airlift assets and about investing or divesting in airfield infrastructure

Modeling and Analyzing the Effect of Ground Refueling Capacity on Airfield Throughput

This thesis develops five analytical models to understand the current ground refueling process, to optimize the airfield configuration and to determine the refueling policy which maximizes throughput, the primary measure of airfield efficiency. This study models the airfield refueling process as a continuous time Markov process to adequately represent the inherent stochastic nature of the transitory ground refueling system and provide an analytical evaluation of various airfield configurations. Also, the study provides an optimal refueling policy to minimize the number of aircraft on the ground which in turn minimizes the average amount of time aircraft spend on the ground in a fifth model, a Markov decision process solved by a linear program. By accomplishing this, higher throughput rates can be achieved by allowing a higher aircraft arrival rate into the airfield

Potential applications of simulation modelling techniques in healthcare: lessons learned from aerospace and military

The Aerospace and Military areas are to do with complex missions and situations. Modelling and Simulation (M&S) has been applied in many areas of defence ranging from space sciences, satellite engineering to multi-warfare (air warfare, undersea warfare), air & missile defence, acquisition, tactical military trainings & exercises, national security analysis and strategic decision making & planning, etc. The application of simulation modelling techniques in healthcare would improve the provision of healthcare services; however, their application has been much relatively feeble in the healthcare sector as compared to the defence sector. This paper presents results from a systematic literature survey on applications of modelling simulation techniques in the Aerospace & Military. The knowledge gained or lessons learned from the survey were finally used to analyze the potential applications of the simulation modelling techniques to the healthcare sector. Results show that in the defence sector, Distributed Simulation has now become a widely adopted technique. However, System Dynamics (SD) and Discrete Event Simulation (DSE) have also gained relative attention. From this survey it becomes clear that various simulation modelling techniques are useful for specific purposes and have potential applications in the healthcare sector

A stochastic program for optimizing military sealift subject to attack

We describe a stochastic program for planning the wartime, sealift deployment of military cargo subject to attack. The cargo moves on ships from US or allied seaports of embarkation through seaports of debarkation (SPODs) near the theater of war where it is unloaded and sent on to final , in-theater destinations. The question we ask is: Can a deployment-planning model, with probabilistic knowledge of the time and location of potential enemy attacks on SPODs, successfully hedge against those attacks? That is, can this knowledge be used to reduce the expected disruption caused by such attacks? A specialized, multi-stage stochastic mixed-integer program is developed and answers that question in the affirmative. Furthermore, little penalty is incurred with the stochastic solution when no attack occurs, and worst-case scenarios are better. In the short term, insight gained from the stochastic-programming approach also enables better scheduling using current rule-based methods

GAME-THEORETIC MODELS FOR RAPID OPERATIONAL AIRLIFT NETWORK DESIGN IN CONTESTED ENVIRONMENTS

The growing threat of conflict with near-peer adversaries requires a robust air-routing plan to transport personnel and cargo effectively. In developing these plans, the U.S. Air Force’s Air Mobility Command (AMC) must account for the dynamic nature of inter-theater operations in a contested environment. Currently, AMC planners predominantly calculate resource allocations manually, which contributes to slower plan implementation and potentially suboptimal solutions. Starting with a proven AMC model, which provides an optimal use of aircraft, cargo allocation, and airfields, we add model features that help determine how to attack this airlift network, optimally delaying the delivery of cargo to operationally relevant locations. The results identify vulnerabilities and provide AMC planners with a prescription of airfield resource allocation that maximizes the movement of cargo. This model delivers a quantitative assessment of an adversary's (whether weather or competitor) ability to delay the mission that can be used to guide policymakers in providing a robust air mobility capability.Outstanding ThesisLieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Central Command Rest and Recuperation Hub-to-Hub Airlift Network Analysis

The primary purpose of this research effort was to discover the efficiency and effectiveness of the historical hub-to-hub R&R airlift network. This study analyzed the hub-to-hub aircraft efficiency rates and introduced capacity changes in the airlift network with the use of Arena simulation to improve network performance. Furthermore, this study created simple heuristic options for the future airlift framework required to meet USCENTCOM\u27s forecasted R&R transportation demand under the premise of a CY11 country 1 drawdown and an upscale of combat and support forces within country 2. There were several important outcomes of this research effort. First, this study designed the future framework for R&R airlift passenger operations with a focus on leveraging simple heuristics to increase intertheater commercial aircraft utilization to 89.7 percent while also adding four additional weekly sorties in the strategic port to intratheater hub routes. As a result, this study demonstrated that passenger velocity at the strategic port could be increased by 20.6 hours on the average and 24.9 hours at the 90th percentile with a decrease in the transient passenger footprint at the strategic port by 215 passengers on the average. This transient passenger footprint reduction also opens up further opportunities for cost savings by contracting support personnel and facilities at the strategic port for future operations. Finally, this study found that the use of a simple heuristic could increase commercial aircraft seat utilization rates by approximately 10 percent yielding an estimated $26.5M in yearly savings in contract airlift

Output Analysis and Comparison of Deployment Models with Varying Fidelity

This thesis explores the changes in insights that result from using different types of models to assess the capability of deploying the Stryker Brigade within specific timeline goals. The thesis uses as its primary base a study conducted in 2002 by USTRANSCOM to evaluate the ability of Stryker to meet stated deployment timeline goals. Specifically, the author compares the outputs from four different models as they change over three different deployment scenarios and 10 different routes. The study investigates the relationships among the outputs of spreadsheet models, spreadsheet models with elements of variability added, and low- and high-level discrete-event simulations. The study also explores the implications of applying newly proposed distributions describing the variability in aircraft cargo loads and en-route ground times. The results of the study suggest that the type of model used to assess a deployment has an effect on the insights derived from exploring scenarios. The study also suggests that the newly proposed ground time distributions have a significant effect on the military\u27s ability to move cargo through an en-route system, and what factors have the greatest limiting effect on the ability of Stryker to meet its deployment timeline goals

Platform Design For Fleet-Level Efficiency Under Uncertain Demand: Application For Military Cargo Aircraft And Fleet

The aircraft system\u27s role in the United Stated Air Force is crucial. For the U.S. Air Force to maintain its air superiority in the world, the constant maintenance, upgrade, and acquisition of the systems must follow. As the cost of fuel rises and with the recent budget situation, the emphasis is on both running the Air Force fleet more efficiently and acquiring the platform that can reduce the fleet level operating cost and the fuel usage and yet brings same capabilities. The approach presented in the thesis combines approaches from multidisciplinary design optimization and operations research to improve energy efficiency-related defense acquisition decisions. The work focuses upon problems that are relevant to the U.S. Air Force-Air Mobility Command (AMC), which is the largest consumer of fuel in the Department of Defense. To reflect AMC problems, the approach must consider the uncertainty in cargo demand; historical data shows that the cargo demand for AMC varies on a daily basis. The approach selects requirements for a new cargo aircraft; predicts size, weight and performance of that new aircraft; and allocates the new aircraft along with existing aircraft fleet to meet the cargo transportation demand. The approach successfully provides a description of a new cargo aircraft that, given the abstractions and assumptions used, will reduce the fleet-level operating cost and / or the fuel needed to meet air cargo demand. The allocation problem incorporates scheduling-like features to account for time driven operational constraints. The results of this study demonstrate the approach for a simple three-route network and 22-base network, using the Global Air Transportation Execution System (GATES) dataset. With addition of uncertainty in demand and random home base generation, the simulation result will suggest an aircraft design that is more flexible to the fluctuations in demand. The 22-base network represents one day of operation of the AMC randomly selected from the GATES data. The result from the 22-base network simulation under uncertain demand scenario for the strategic fleet suggests the introduction of five new aircraft that are capable of 24 pallets and 3,300 nautical miles of unrefueled design range which will save 1.10 percent in the expected direct operating cost and 4.20 percent in expected fuel usage compared to the baseline allocation result without introduction of the new aircraft

Simulation Evaluation of the Combat Value of a Standoff Precision Airdrop Capability

This project is a simulation evaluation of the developmental standoff precision airdrop (SOPAD) capability. SOPAD is a new technology under consideration to deliver supplies to forward-deployed units using either a semi-rigid wing or a guided parafoil. These delivery systems allow airdrop of supplies from altitudes of 25,000 feet and distances 25 miles from the delivery point. Using global positioning system guidance, on board navigational computers, and automatic steering mechanisms, the delivery system flies to the target following a designated flight plan. The concept includes delivering supplies to remote and potentially hostile areas without endangering the supply aircraft. In addition, supplies can be delivered to multiple locations from a single aircraft. The Air Force\u27s THUNDER model was used to simulate the SOPAD capability and observe the impact in the simulated combat environment. The scenario places a light infantry brigade in a position where supply by ground is prohibited due to terrain limitations and it must hold its position until relief forces are available. The unit must fight for a one-week period being resupplied only through airdrop. The results of the simulation are measured through aircraft attrition, unit strength, forward line of troops movement, and the supplies delivered to the unit