Integrating the fleet assignment model with uncertain demand

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.One of the main challenges facing the airline industry is planning under uncertainty, especially in the context of schedule disruptions. The robust models and solution algorithms that have been proposed and developed to handle the uncertain parameters will be discussed. Fleet assignment models (FAM) are used by many airlines to assign aircraft to fights in a schedule to maximize profit. In the context of FAM, the goal of robustness is to produce solutions that perform well relative to uncertainties in demand and operation. In this thesis, we introduce new FAMs (i.e. DFAM1 and DFAM2) that tackles the common problem associated with aircraft utilization. Subsequently, stochastic programming (SP) is presented as a method of choice for the research. Through the use of a two-stage SP with recourse technique, the DFAMs are extended to SP-FAMs (SP-FAM1 and SP-FAM2). The main distinction of the SP-FAM compared with other FAMs is that, given a stochastic passenger demand, it gives a strategic fleet assignment solution that hedges against all possible tactical solutions. In addition, we have a tactical solution for every scenario. In generating the demand scenarios, we use a network-simulation model embedded with a time-series engine that gives a snapshot of one week that is representative of any other week of the scheduling season. We later outline the approach of solving the SP-FAMs where the schedule is compacted through several preprocessing steps before inputting it into SAS-AMPL converter. The SAS-AMPL converter prepares all the data into readable AMPL format. Finally, we execute the optimizer using a FortMP solver (integrated in AMPL) that invokes branch-and-bound algorithm. We give a proof of concept using real data from a Middle East airline. Our investigations establish clear benefits of the recourse FAM compared to alternative models. Finally, we propose areas of future research to improve SP-FAM robustness through solution algorithms, revenue management (RM) effects, calibration of network-simulation models and system integration

Future aircraft networks and schedules

This thesis has focused on an aircraft schedule and network design problem that involves multiple types of aircraft and flight service. First, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. Then, this thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch. After developing models in the three steps and creating large-scale instances of these models, this dissertation develops iterative algorithms and subproblem approaches to solving these instances, and it presents computational results of these large-scale instances. To validate the models and solution algorithms developed, this thesis compares the daily flight schedules that it designed with the schedules of the existing airlines. In addition, it discusses the implication of using new aircraft in the future flight schedules. Finally, future research in three areas--model, computational method, and simulation for validation--is proposed.Ph.D.Committee Chair: Johnson, Ellis; Committee Co-Chair: Clarke, John-Paul; Committee Member: Ergun, Ozlem; Committee Member: Nemirovski, Arkadi; Committee Member: Smith, Barr

Aircraft Maintenance Routing Problem – A Literature Survey

The airline industry has shown significant growth in the last decade according to some indicators such as annual average growth in global air traffic passenger demand and growth rate in the global air transport fleet. This inevitable progress makes the airline industry challenging and forces airline companies to produce a range of solutions that increase consumer loyalty to the brand. These solutions to reduce the high costs encountered in airline operations, prevent delays in planned departure times, improve service quality, or reduce environmental impacts can be diversified according to the need. Although one can refer to past surveys, it is not sufficient to cover the rich literature of airline scheduling, especially for the last decade. This study aims to fill this gap by reviewing the airline operations related papers published between 2009 and 2019, and focus on the ones especially in the aircraft maintenance routing area which seems a promising branch

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

Integrated schedule planning with supply-demand interactions

We present an integrated schedule planning model where the decisions of schedule design, fleeting and pricing are made simultaneously. Pricing is integrated through a logit demand model where itinerary choice is modeled by defining the utilities of the alternative itineraries. Utilities are explained with the fare price, departure time and number of stops. Spill and recapture effects are incorporated in the model to better represent the demand. For the recapture ratios we use a logit formulation similar to the demand model so that the ratios are determined by the model according to the utilities of the alternatives. Furthermore fare class segmentation is considered in such a way that the model decides the seats allocated to each fare class. To deal with the high complexity of the resulting mixed integer nonlinear problem, we propose a heuristic algorithm based on Lagrangian relaxation and sub-gradient optimization. The study is in the context of a project regarding the design of an innovative air transportation system called Clip-Air which has flexible transportation capacity. In order to quantify the potential advantages of this new system, models are extended to work with Clip-Air fleet and comparative analysis is carried out using a dataset for a major European company. It is observed that, the enhanced flexibility of Clip-Air allows to transport around 15% more passengers with the same overall fleet capacity

Increasing Collegiate Flight Training Fleet Utilization Through the Use of an Aircraft Assignment Algorithm

The operational efficiency of fleet aircraft employed for student flight training in collegiate aviation programs is strongly influenced by scheduling, among other factors. The average utilization rate for the fleet operated by the Purdue University School of Aviation and Transportation Systems was found to be 24% (Avery, 2014), and there is no data to suggest that that this rate is atypical in similar institutional programs. Mott and Bullock (2015) identified several means by which the utilization rate could be increased, and improvements in the dispatch and scheduling process were a key component of those recommendations. This article describes a scheduling algorithm that was implemented at Purdue University in the fall semester of 2015. The algorithm is a linear programming technique that incorporates optimization constraints unique to collegiate flight training operations. The resulting improvements in aircraft utilization will facilitate an increased matriculation rate of students into the flight program, thereby allowing the allocation of fixed costs over a wider user base and the reduction of overall program fees for all students. Those improvements are validated through measurement of the reduction of the cumulative turn times between aircraft operations

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

Empirical investigations of properties of robust aircraft routing models

The airline schedule planning process is an important component of airline operations, and it involves considerably complex problems. This research focuses on the aircraft routing phase. We introduce the concept of robustness in aircraft routing problems, and find solutions that can stand uncertainty. We categorize the delays in flight operations into two components – independent delay and propagated delay. In the data driven approach, independent delay can be regarded as constant, but propagated delay can be worked on. An example of aircraft swap is given to show that aircraft routing can potentially reduce the flight delays. To solve robust aircraft routing problems, we propose a list of formulations. They are in three categories – Lan, Clarke, Barnhart’s approach, chance-constrained programming approach, and extreme value approach. We conduct experiments with two airline networks – a 50-flight network and a 165-flight network. The K-fold cross validation approach is incorporated into aircraft routing problems to eliminate overfitting. According to the three evaluation metrics – on time performance, average total propagated delay and passenger disruptions, several good formulations are identified, which are recommended for airline schedule planners. We also explain the reasons behind the solution differences