Airline Schedule Planning Research Articles

Schedule-level optimization of flight block times for improved airline schedule planning: A data-driven approach

The development of flight block time schedules for future airline operations is a critical aspect of the schedule development process. It involves determining the appropriate gate-to-gate time for each flight to optimize on-time performance and ensure efficient utilization of flight resources. This article presents a modeling framework that addresses the airlines' scheduled block time (SBT) design problem. The framework employs a novel data-driven optimization model that incorporates reliability measures at both the flight and schedule levels. This approach enables airline schedule planners to assess the relationship between the allocated SBT for each flight and the overall schedule reliability, and make informed decisions regarding the trade-off between schedule reliability and operational costs. Experiments show that the proposed methodology outperforms real-world SBT plans implemented by two major U.S. airlines, demonstrating its superiority. The results of this comparison indicate that the developed framework could assist airlines in improving reliability while deploying the same block time budget or in eliminating unnecessary slack in their schedules while achieving their targeted reliability, resulting in significant cost savings.

Modeling and optimizing the delay propagation in Chinese aviation networks.

We define metrics to quantify the level of overall delay and propose an agent-based data-driven model with four factors, including aircraft rotation, flight connectivity, scheduling process, and disturbance, to build a simulator for reproducing the delay propagation in aviation networks. We then measure the impact on the propagation by the delay at each airport and analyze the relevance to its temporal characteristics. When delay occurs, airline schedule planning may become infeasible, and rescheduling of flights is usually required to maintain the function of the system, so we then develop an improved genetic algorithm (GA) to reschedule flights and to relax the root delay. Results indicate that priority-based strategy rather than First-Come-First-Serve can achieve minimum overall delay when congestion occurs, and aircraft rotation is the most important internal factor contributing to delay propagation. Furthermore, the reschedule generated by the improved GA can decrease delay propagation more significantly compared to the agent-based model.

Airline schedule planning: a review and future directions

PurposeThe purpose of this paper is twofold: first to carry out a comprehensive literature review for state of the art regarding airline schedule planning and second to identify some new research directions that might help academic researchers and practitioners.Design/methodology/approachThe authors mainly focus on the research work appeared in the last three decades. The search process was conducted in database searches using four keywords: “Flight scheduling,” “Fleet assignment,” “Aircraft maintenance routing” (AMR), and “Crew scheduling”. Moreover, the combination of the keywords was used to find the integrated models. Any duplications due to database variety and the articles that were written in non-English language were discarded.FindingsThe authors studied 106 research papers and categorized them into five categories. In addition, according to the model features, subcategories were further identified. Moreover, after discussing up-to-date research work, the authors suggested some future directions in order to contribute to the existing literature.Research limitations/implicationsThe presented categories and subcategories were based on the model characteristics rather than the model formulation and solution methodology that are commonly used in the literature. One advantage of this classification is that it might help scholars to deeply understand the main variation between the models. On the other hand, identifying future research opportunities should help academic researchers and practitioners to develop new models and improve the performance of the existing models.Practical implicationsThis study proposed some considerations in order to enhance the efficiency of the schedule planning process practically, for example, using the dynamic Stackelberg game strategy for market competition in flight scheduling, considering re-fleeting mechanism under heterogeneous fleet for fleet assignment, and considering the stochastic departure and arrival times for AMR.Originality/valueIn the literature, all the review papers focused only on one category of the five categories. Then, this category was classified according to the model formulation and solution methodology. However, in this work, the authors attempted to propose a comprehensive review for all categories for the first time and develop new classifications for each category. The proposed classifications are hence novel and significant.

Robust Airline Schedule Planning: Minimizing Propagated Delay in an Integrated Routing and Crewing Framework

For reasons of tractability, the airline scheduling problem has traditionally been sequentially decomposed into various stages (e.g., schedule generation, fleet assignment, aircraft routing, and crew pairing), with the decisions from one stage imposed upon the decision making process in subsequent stages. Although this approach greatly simplifies the solution process, it unfortunately fails to capture the many dependencies between the various stages, most notably between those of aircraft routing and crew pairing, and how these dependencies affect the propagation of delays through the flight network. Because delays are commonly transferred between late running aircraft and crew, it is important that aircraft routing and crew pairing decisions are made together. The propagated delay may then be accurately estimated to minimize the overall propagated delay for the network and produce a robust solution for both aircraft and crew. In this paper we introduce a new approach to accurately calculate and minimize the cost of propagated delay in a framework that integrates aircraft routing and crew pairing.

Integrated Robust Airline Schedule Development

In air transportation, airline profitability is influenced by the airline's ability to build flight schedules. In order to generate operational schedules, airlines engage in a complex decision-making process, referred to as airline schedule planning. Up to now, the generation of flight schedules has been separated and optimized sequentially. The schedule design has been traditionally decomposed into two sequential steps. The frequency planning and the timetable development. The purpose of the second problem of schedule development, fleet assignment, is to assign available aircraft types to flight legs such that seating capacity on an assigned aircraft matches closely with flight demand and such that costs are minimized. Our work integrates these planning phases into one single model in order to produce more economical solutions and create fewer incompatibilities between the decisions. We propose an integrated robust approach for the schedule development step. We design the timetable ensuring that enough time is available to perform passengers’ flight connections, making the system robust avoiding misconnected passengers. An application of the model for a simplified IBERIA network is shown.

Monitoring Aircraft Turnaround Operations – Framework Development, Application and Implications for Airline Operations

A real-time operation monitoring system – Aircraft Turnaround Monitoring System – is developed based on a system framework to monitor aircraft turnaround operations at an airport. Mobile computing devices (PDAs) and wireless network technology General Packet Radio Service (GPRS) are used to implement the real-time monitoring system for an airline. System implementation and test results indicate that real-time operation monitoring can potentially reduce delays occurring from airline operations. Proactive measures can be taken immediately by ground handling staff to reduce delays, once the risk of delays and potential delay propagation is identified. The availability of detailed operating data can help airlines identify the root delay causes from complex connections among aircraft, flight/cabin crew and passengers. In addition, these operating data also shed some light on the future development of aircraft routing algorithms in order to consider explicitly stochastic disruptions and delay propagation in airline schedule planning.

Airline Schedule Planning: Integrated Models and Algorithms for Schedule Design and Fleet Assignment

Constructing a profitable schedule is of utmost importance to an airline because its profitability is critically influenced by its flight offerings. We focus our attention on the steps of the airline schedule planning process involving schedule design and fleet assignment. Airline schedule design involves determining when and where to offer flights such that profits are maximized, and fleet assignment involves assigning aircraft types to flight legs to maximize revenue and minimize operating cost. We present integrated models and solution algorithms that simultaneously optimize the selection of flight legs for and the assignment of aircraft types to the selected flight legs. Preliminary results, based on data from a major U.S. airline, suggest that significant benefits can be achieved.

Airline Schedule Planning: Accomplishments and Opportunities

Plagued by high labor costs, low profitability margins, airspace and airport congestion, high capital and operating costs, security and safety concerns, and complex and large-scale management and operations decisions, the airline industry has armed its planners with sophisticated optimization tools to improve decision making and increase airline profits. In this paper, we describe optimization approaches for airline schedule planning, demonstrating how optimization can facilitate the management of a diverse and finite set of expensive, highly constrained resources. We focus on the art and science of modeling and solving these problems, providing illustrative examples of the associated impacts and challenges, and highlighting effective techniques that might be applicable to problems arising in other industries.

Airline Schedule Planning by Genetic Algorithms

Airline Schedule Planning by Genetic Algorithms

Preface: Mathematics of Industrial Systems III

The goal of the series "Mathematics of Industrial Systems" (MIS) is to describe and promote the role of applied mathematics in industrial systems. In particular, the publication focuses on discrete models and combinatorial solution approaches in industry, where the term industry should be understood in a broad sense.The third volume of this series contains fourteen contributions. The papers describe successful applications of mathematics to applied problems and propose new solution procedures. Two papers deal with interesting applications in telecommunication, namely network synthesis problems and frequency assignment for cellular phone networks. Further articles describe an efficient routing of helicopters for crew exchange, stowage planning for container ships, and mathematical tools in airline schedule planning. Several papers deal with aspects of production processes, starting from dynamic facility layout and the design and operation of AGV-served manufacturing systems, via matching of assembly operations, material planning and tool allocation to certain aspects of scheduling problems.Many people have helped in the preparation of this third volume of MIS. In particular, we would like to thank the referees for their careful work and thoughtful remarks. Their efforts substantially improved the quality of this volume. Moreover, our appreciation is due to Mrs. Nelly Segal, RUTCOR, for providing much help to the editors and for handling editorial matters in such an excellent way.The fourth volume of this series is already in preparation. Submissions for this or another forthcoming volume in the series can be sent to any of the editors. Moreover, comments and proposals for future volumes are welcome and appreciated by the editors.

Mathematical models in airline schedule planning: A survey

The schedule is an airline's primary product, having the most influence (along with price) on a passenger's choice of an airline. Once an airline decides (at least tentatively) on a schedule, a host of related problems have to be resolved before it can consider the schedule feasible, and can proceed to market the schedule. Among these problems are traffic forecasting and allocation that forecasts traffic on each flight leg for use in the fleet assignment model, fleet assignment that decides the fleet type of the aircraft flying the legs in the schedule, equipment swapping to change an assigned equipment type on a leg if and when necessary, through flight selection for determining which pairs of flights to market as one-stops (without any aircraft change), maintenance routing that develops aircraft rotations to provide adequate opportunities for overnight maintenance, and flight numbering to number flights as consistently as possible with a prior schedule. Considerable methodological and computational advances have been made in the recent past in developing models and solution methods for almost all of the problems mentioned above. In this paper we survey these various models and solution techniques.

Decision Support for Airline Schedule Planning

Since the 1950s, the operations research community has developed a large number of computer models to aid in the solution of airline scheduling problems. One notable characteristic of these contributions is that each algorithm was developed with its own input and output structures, user interface, and hardware and software requirements. The result is that many of these contributions are under-utilized because they are cumbersome to use, not integrated with the other airline's systems, and not connected across all functions of the airline (from planning to operations control). What was needed to make these contributions effective was a scheduling “environment” with a systematic interaction between the human, standardized databases across all functions of the airline, powerful desktop workstations for decision support, a standardized interactive graphical user interface for schedule editing, and the operations research techniques for optimization. This paper reports on the application of the integration of computer science and operations research in a decision support system for airline schedule planning. The application integrates a graphical user interface and the database with the schedule optimization algorithms.