Application of stochastic programming techniques to airline scheduling

The goal of this project was to evaluate the effectiveness of stochastic programming techniques when applied to the airline scheduling process to reduce the effect of stochastic flight delays. A variety of traditional and stochastic programming models were developed for generating flight schedules. The resultant flight schedules were tested using simulations to evaluate their performance in real-world conditions with regard to flight delays, and their effects on the schedule’s operations. It was found that stochastic programming techniques were able to improve the delay recovery performance of the schedules at the cost of decreasing the schedule’s profit; and that flight schedules which are more dense with flight activity are affected more by the stochastic programming techniques. The use of stochastic programming techniques is recommended for the cases where an airline’s flight schedule has a high density of activity and the negative effects of flight delays needs to be minimized

Quantum Computing for Airline Planning and Operations

Classical algorithms and mathematical optimization techniques have beenused extensively by airlines to optimize their profit and ensure that regulationsare followed. In this thesis, we explore which role quantum algorithmscan have for airlines. Specifically, we have considered the two quantum optimizationalgorithms; the Quantum Approximate Optimization Algorithm(QAOA) and Quantum Annealing (QA). We present a heuristic that integratesthese quantum algorithms into the existing classical algorithm, whichis currently employed to solve airline planning problems in a state-of-the-artcommercial solver. We perform numerical simulations of QAOA circuits andfind that linear and quadratic algorithm depth in the input size can be requiredto obtain a one-shot success probability of 0.5. Unfortunately, we areunable to find performance guarantees. Finally, we perform experiments withD-wave’s newly released QA machine and find that it outperforms 2000Q formost instances

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

ERAU Graduate Catalog 1990 - 1991

The Embry-Riddle Aeronautical University Graduate Course Catalog 1990 - 1991.https://commons.erau.edu/erau-course-catalog/1063/thumbnail.jp

Operational research:methods and applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Operational Research: methods and applications

This is the final version. Available on open access from Taylor & Francis via the DOI in this recordThroughout its history, Operational Research has evolved to include methods, models and algorithms that have been applied to a wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first summarises the up-to-date knowledge and provides an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion and used as a point of reference by a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

Three essays on delay management for passenger rail services

Railways are confronted with several problems in their daily business. One of these operational problems is delay management. Therein the question of whether a train should wait for a delayed feeder train or depart on time is addressed. Answering this question is not trivial since the determined wait-depart decision may cause serious consequences. While the majority of models in the literature usually take the decision by aiming for minimizing disturbances in the operating procedure, delay management focuses on the impact for passengers. By minimizing passenger delay, delay management differs from the other problems on the operational level and leads to different recommendations for dispatchers. This thesis puts the scope on railway delay management and its impacts for passengers. It consists of three essays: a literature review on delay management and two models that advance the research in this field. In the literature review, a new classification scheme for operational problems in railways is developed. Literature in delay management and influence from delay management on neighboring areas are discussed. The second essay proposes a stochastic dynamic programming approach taking the dynamic nature of delays and uncertainty into account. Evaluating potential recourse actions derives policies for taking dispatching decisions. The third essay considers the capacity of trains in the decision making process. Rerouting of passengers for broken connections is further assumed and spill effects for passenger streams are measured. A nonlinear model is developed and solved by linearizing it exactly and heuristically. Both approaches, from the second and third essay, are evaluated in a numerical study on real-world data from the German railway provider Deutsche Bahn. Germany possesses a rather complex and massive railway network that will require further decision support and future research

United States Air Force fighter jet maintenance Models : effectiveness of index policies

Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2013.Cataloged from PDF version of thesis. "June 2013."Includes bibliographical references (pages 107-109).As some of the most technically complex systems in the world, United States fighter aircraft require a complex logistics system to sustain their reliable operation and ensure that the day-to-day Air Force missions can be satisfied. While there has been a lot of attention among academics and practitioners regarding the study of this complex logistics system, most of the focus has been on availability of spare parts that are indeed essential for the smooth operations of the fighter aircraft. However, in recent years there has been an increasing awareness that maintenance resources are an equally important enabler and should be considered together with inventory issues. The maintenance resources required to repair the fighter aircraft are expensive and therefore limited. Moreover, there are various types of maintenance that compete for the same resources. It .is therefore imperative that the allocation of maintenance resources is done as efficiently as possible. In this thesis, we study two areas of fighter aircraft maintenance that could significantly benefit from improved resource allocation and scheduling strategies. We use quantitative and qualitative data from Air Force data-bases and logistics personnel to develop an innovative modeling framework to capture these challenging maintenance problems. This modeling framework is based on a generalization of the of the well-known multi-armed bandit superprocess problem. Using these models, we develop index policies which provide intuitive, easily implemented, and effective rules for scheduling maintenance activities and allocating maintenance resources. These policies seem to improve on existing best practices within the Air Force, and perform well in extensive data-driven simulated computational experiments. The first area is focused on the challenges of scheduling maintenance for the low observable (stealth) capabilities of the F-22 Raptor, specifically, maintenance of the outer coating of the aircraft that is essential to maintain its radar invisibility. In particular, we generate index policies that efficiently schedule which aircraft should enter low observable maintenance, how long they should be worked on, and which aircraft should fly in order to maximize the stealth capability of the fleet. Secondly, we model the maintenance process of the F100-229 engine, which is the primary propulsion method used in the F-16C/D and F-15E aircraft. In particular, we generate index policies to decide which engines should take priority over others, and whether or not certain components of the engines should be repaired or replaced. The policies address both elective (planned) and unplanned maintenance tasks.by John M. Kessler.S.M