A Rolling Horizon Based Algorithm for Solving Integrated Airline Schedule Recovery Problem

Airline disruption incurred huge cost for airlines and serious inconvenience for travelers. In this paper, we study the integrated airline schedule recovery problem, which considers flight recovery, aircraft recovery and crew recovery simultaneously. First we built an integer programming model which is based on traditional set partitioning model but including flight copy decision variables. Then a rolling horizon based algorithm is proposed to efficiently solve the model. Our algorithm decomposes the whole problem into smaller sub-problems by restricting swapping opportunities within each rolling period. All the flights are considered in each sub-problem to circumvent ‘myopic’ of traditional rolling horizon algorithm. Experimental results show that our method can provide competitive recovery solution in both solution quality and computation time.published_or_final_versio

An Irregular Flight Scheduling Model and Algorithm under the Uncertainty Theory

The flight scheduling is a real-time optimization problem. Whenever the schedule is disrupted, it will not only cause inconvenience to passenger, but also bring about a large amount of operational losses to airlines. Especially in case an irregular flight happens, the event is unanticipated frequently. In order to obtain an optimal policy in airline operations, this paper presents a model in which the total delay minutes of passengers are considered as the optimization objective through reassigning fleets in response to the irregular flights and which takes into account available resources and the estimated cost of airlines. Owing to the uncertainty of the problem and insufficient data in the decision-making procedure, the traditional modeling tool (probability theory) is abandoned, the uncertainty theory is applied to address the issues, and an uncertain programming model is developed with the chance constraint. This paper also constructs a solution method to solve the model based on the classical Hungarian algorithm under uncertain conditions. Numerical example illustrates that the model and its algorithm are feasible to deal with the issue of irregular flight recovery

Disruption management

The main objective of this project is to model the ARP (Aircraft Recovery Problem) from a constraint programming (CP) point of view. The information required for this project is extracted from previous papers that cope with the problem using heuristics, metaheuristics or using network-models. Also, two scenarios will be tested to verify that the implementation is correct

Weighted Time-Band Approximation Model for Flight Operations Recovery considering Simplex Group Cycle Approaches in China

The time-band approximation model for flight operations recovery following disruption (Bard, Yu, Arguello, IIE Transactions, 33, 931–947, 2001) is constructed by partitioning the recovery period into time bands and by approximating the delay costs associated with the possible flight connections. However, for disruptions occurring in a hub-and-spoke network, a large number of possible flight connections are constructed throughout the entire flight schedule, so as to obtain the approximate optimal. In this paper, we show the application of the simplex group cycle approach to hub-and-spoke airlines in China, along with the related weighted threshold necessary for controlling the computation time and the flight disruption scope and depth. Subsequently, we present the weighted time-band approximation model for flight operations recovery, which incorporates the simplex group cycle approach. Simple numerical experiments using actual data from Air China show that the weighted time-band approximation model is feasible, and the results of stochastic experiments using actual data from Sichuan Airlines show that the flight disruption and computation time are controlled by the airline operations control center, which aims to achieve a balance between the flight disruption scope and depth, computation time, and recovery value

Aircraft route recovery based on distributed integer programming method

In order to further promote the application and development of unmanned aviation in the manned field, and reduce the difficulty that airlines cannot avoid due to unexpected factors such as bad weather, aircraft failure, and so on, the problem of restoring aircraft routes has been studied. To reduce the economic losses caused by flight interruption, this paper divides the repair problem of aircraft operation plans into two sub problems, namely, the generation of flight routes and the reallocation of aircraft. Firstly, the existing fixed-point iteration method proposed by Dang is used to solve the feasible route generation model based on integer programming. To calculate quickly and efficiently, a segmentation method that divides the solution space into mutually independent segments is proposed as the premise of distributed computing. The feasible route is then allocated to the available aircraft to repair the flight plan. The experimental results of two examples of aircraft fault grounding and airport closure show that the method proposed in this paper is effective for aircraft route restoration

A Model for aircraft recovery problem

Thesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Mobile Telecommunication and Innovation at (MSc.MTI) at Strathmore UniversityIn the airline industry, a myriad of uncertain events take place that lead to the disruption of original flight schedules. Such events include mechanical failure, technical challenges, weather changes, airport and crew related issues. Airlines therefore need a robust, dynamic way of recovering their schedules during disruptions in order to remain profitable. In recovery scenarios, aircraft recovery is given the highest priority since aircraft are the scarcest and most utilised resources in the airline. A mathematical model for airline schedule recovery that recovers aircrafts was presented in this study. The model is based on defining a recovery scope once a fleet of aircraft has been disrupted. The model examines the possibility of delaying the flights for a short period, reassigning aircraft, ferrying aircraft and also cancelling flights. The objective of the model is to minimise costs associated with assigning a different aircraft to the disrupted flight leg, delay costs, cancellation costs for business class passengers, cancellation costs for economy class passengers and ground costs. This study uses real time data from Kenya Airways to test the proposed model. A decision support system was then developed and deployed to the Integrated Operations Control Centre in Kenya Airways for use by the duty managers to come up with optimal solutions with the least cost implications to the airline

Airline schedule recovery concept and model

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2003.Includes bibliographical references (leaves 61-62).Inclement weather at an airline's hub airport can be devastating to that airline's schedule. The repercussions resonate throughout the airline's network as capacity is reduced, connections are missed, and passengers are delayed on a larger scale than during irregular operations at a spoke airport. The main hypothesis behind the work presented in this thesis is that by shifting a small fraction of a connecting bank to strategically located, under-utilized airports during irregular operations, an airline can reduce costs and aircraft delays relative to current industry rescheduling practices. These proposed "virtual hubs" would, in addition to hosting selected connecting traffic that is shifted from the original hub in order to maximize passenger flow through the network, also reduce the demand on the nominal hub airport. The primary goal of this research project was to develop methods for the implementation of a virtual hub network and evaluate the potential benefits to the airline industry. To that end, a mathematical formulation is presented along with a case study of the benefits of a virtual hub to a major US airline. The actual recovered schedule and delay statistics for a day of irregular operations was compared to the results from the virtual hub network. Results indicate that significant passenger delays are reduced 94% and flight cancellations are reduced by 15% when a virtual hub network is implemented.by Michelle J. Karow.S.M