Departure Delays Research Articles

Effect of airline choice and temporality on flight delays

The civil aviation industry is critical to the economic development of any nation. Being a key infrastructure service, the performance of the civil aviation industry spills over to other segments of the economy. We investigate service failure among US airlines, using departure delay, and model its likelihood using mixed-logit regression. We characterize arrival performance for delayed departures using a service recovery/double deviation framework. We model the likelihood of different arrival possibilities using multinomial logistic regression. We use the chosen airline, temporality, and flight duration as predictors. Our key results include: (i) Afternoon/evening flights, and longer duration flights are more likely to depart late; (ii) Delta Airlines is most likely to depart on time; (iii) Southwest Airlines is best in recovering from delayed departures; (iv) United Airlines is most likely to aggravate delays.

A Methodology for Predicting Aggregate Flight Departure Delays in Airports Based on Supervised Learning

This paper proposes a new methodology for predicting aggregate flight departure delays in airports by exploring supervised learning methods. Individual flight data and meteorological information were processed to obtain four types of airport-related aggregate characteristics for prediction modeling. The expected departure delays in airports is selected as the prediction target while four popular supervised learning methods: multiple linear regression, a support vector machine, extremely randomized trees and LightGBM are investigated to improve the predictability and accuracy of the model. The proposed model is trained and validated using operational data from March 2017 to February 2018 for the Nanjing Lukou International Airport in China. The results show that for a 1-h forecast horizon, the LightGBM model provides the best result, giving a 0.8655 accuracy rate with a 6.65 min mean absolute error, which is 1.83 min less than results from previous research. The importance of aggregate characteristics and example validation are also studied.

Enhancement for human resource management in the ULD build-up process of air-cargo terminal: a strategic linkage approach

This study proposes a strategic linkage method with mathematical model, simulation model and heuristic approaches to an adaptive workforce scheduling problem reflecting the work site situation of the air cargo terminal. For the application of the proposed method, we first generate an initial workforce schedule using the optimization model for minimizing labor costs. The simulation model is then used to verify that the initial schedule is applicable on-site. If the initial plan does not meet the service level expressed as a delay in the departure of aircrafts, by linking optimization and simulation models, additional required personnel are determined for reducing the frequency of departure delay. But, though the experiments, we were able to confirm that the linkage of optimization and simulation alone resulted in the creation of excess manpower. To compensate for the limitation of the linkage, we develop the Backward Removal Heuristics (BRHs) algorithm. In an experiment with BRHs algorithm, we showed that BRHs could reduce the number of unnecessarily added workers based on the interaction between utilization of workers and operation congestion. With case study on the ULD build-up process of K airline air-cargo terminal, the linkage model with BRHs algorithm is tested and proven its effectiveness. The experimental results show that the workforce schedule from the linkage model increases the service level and the cost, but when applied to the BRHs algorithm, the model maintains the service level but decreases the cost.

Train punctuality analysis in a rolling stock perspective

This paper studies how time delays spread through the railway system. We evaluate timetable and rolling stock interaction in relation to medium size delays. In particular, we study the connection between arrival and departure delays for trains that are operated by the same rolling stock individual. We studied one year of data for trains circulating in the Oslo area.Research questions in this study are:What is the connection between arrival and departure delays for the same piece of rolling stock?How can delays be tracked through the route schedules and the rolling stock circulation plan?Punctuality analysis was performed to investigate if there is a connection between arrival and departure delays. A correlation analysis of the arrival delays and the corresponding departures was done in order to find the possible connection.There was a connection between the size of arrival delays and the size of the corresponding departure delays. We found a threshold at around 20 minutes. An arrival delay over this threshold is expected to cause departure delays. Below the threshold most of the arrival delays are absorbed.

Competition and Quality: Evidence from High-Speed Railways and Airlines

The entry of High-Speed Railways (HSR) represents a disruptive competition to airlines, particularly for short- to medium-distance journeys. Utilizing a unique dataset that contains the details of all flights departing from Beijing to 113 domestic destinations in China since January 2009, we employ a difference-in-differences approach to examine the effects of HSR entry on the quality of service provided by airlines as proxied by their on-time performance, and to identify the channels through which competition leads to quality improvement. We document two main findings. First, the competition from the entry of HSR leads to significant reductions in the mean and variance of travel delays on the affected airline routes. Second, the reductions in departure delays--which are controlled mostly by airlines, and the duration of taxi-in time--which are controlled mostly by destination airports, are identified as the main sources of the improvement in the airlines' on-time performance.

Competition and Quality: Evidence from High-Speed Railways and Airlines

The entry of High-Speed Railways (HSR) represents a disruptive competition to air-lines, particularly for short- to medium-distance journeys. Utilizing a unique dataset that contains the details of all ?ights departing from Beijing to 113 domestic desti-nations in China since January 2009, we employ a di?erence-in-di?erences approach to examine the e?ects of HSR entry on the quality of service provided by airlines as proxied by their on-time performance, and to identify the channels through which competition leads to quality improvement. We document two main ?ndings. First, the competition from the entry of HSR leads to signi?cant reductions in the mean and variance of travel delays on the a?ected airline routes. Second, the reductions in departure delays–which are controlled mostly by airlines, and the duration of taxi-in time–which are controlled mostly by destination airports, are identi?ed as the main sources of the improvement in the airlines’ on-time performance.

Identification and empirical characterisation of flight arrival variation and the impact on departure punctuality

In this paper, based on field data from two years of operations at a European Airport, empirical evidence of the influence of arrival variation on departure delay flight for short scheduled ground times (i.e., up to 60 minutes) is revisited, including 'on time', 'early' and 'late' arrivals. For early and late arrivals, variation is measured together with the extension of the scheduled ground time, and the numbers of departure delay minutes recorded for the next departure are considered. Based on the results obtained, it is provided a quantitative method to identify the effects of early and late arrivals on airport operations, its magnitude is dependent of airport's dynamic factors such demand and capacity and its operational context. For the study case presented early arrivals are shown to generate higher airport operational disturbances compared with late arrivals that allow better reaction capacity to compensate with direct effects on turnaround time process.

Identification and empirical characterisation of flight arrival variation and the impact on departure punctuality

In this paper, based on field data from two years of operations at a European Airport, empirical evidence of the influence of arrival variation on departure delay flight for short scheduled ground times (i.e., up to 60 minutes) is revisited, including 'on time', 'early' and 'late' arrivals. For early and late arrivals, variation is measured together with the extension of the scheduled ground time, and the numbers of departure delay minutes recorded for the next departure are considered. Based on the results obtained, it is provided a quantitative method to identify the effects of early and late arrivals on airport operations, its magnitude is dependent of airport's dynamic factors such demand and capacity and its operational context. For the study case presented early arrivals are shown to generate higher airport operational disturbances compared with late arrivals that allow better reaction capacity to compensate with direct effects on turnaround time process.

A High-speed Train Timetable Rescheduling Approach in case of Disturbances

This paper from a macroscopic viewpoint develops a train timetable rescheduling approach on a single high-speed railway line under disturbances, i.e. inevitable train delays in the duration of the train operation. A mixed-integer linear programming model is formulated to minimize the arrival delay and the departure delay altogether. The commercial optimization software CPLEX is adopted in an effort to seek the optimal solution in an acceptably short time required in the real-time rescheduling process. The proposed approach is further tested on a real-world case study and the numerical results show that compared with the results obtain by the traditional genetic algorithm, using CPLEX to solve the model can yield better solutions and consume the desired computation time, thereby demonstrating its effectiveness and efficiency.

Impacts of unplanned aircraft diversions on airport ground operations

When an unplanned disruption causes the temporary closure of an airport, incoming flights are re-routed to one (or more) nearby ones. As a consequence, traffic in the alternate airport increases and the efficiency, punctuality and regularity of operations may be compromised. The purpose of this work is to determine the impacts on the alternate airport airside operations due to the presence of diverted flights. If the number of aircraft to be serviced increases, ground handling operators are subjected to an additional workload, probably resulting in delayed departures and knock-on delays. A discrete-event simulation model of both aircraft landing-and-takeoff (LTO) cycles and turnaround operations is built by using AnyLogic. The model is applied to the case study of Lisbon “Humberto Delgado” airport. When the number of incoming flights increases upon a certain threshold, departure delays spread over the day, which should call for emergency actions and contingency plans.

A Method of Reducing Flight Delay by Exploring Internal Mechanism of Flight Delays

This paper explores the internal mechanism of flight departure delay for the Delta Air Lines (IATA-Code: DL) from the viewpoint of statistical law. We roughly divide all of delay factors into two sorts: propagation factor (PF), and nonpropagation factors (NPF). From the statistical results, we find that the distribution of the flight departure delay caused by only NPF exhibits obvious power law (PL) feature, which can be explained by queuing model, while the original distribution of flight departure delay follows the shift power law (SPL). The mechanism of SPL distribution of flight departure delay is considered as the results of the aircraft queue for take-off due to the airports congestion and the propagation delay caused by late-arriving aircraft. Based on the above mechanism, we develop a specific measure for formulating flight planning from the perspective of mathematical statistics, which is easy to implement and reduces flight delays without increasing operational costs. We analyze the punctuality performance for 10 of the busiest and the highest delay ratio airports from 155 airports where DL took off and landed in the second half of 2017. Then, the scheduled turnaround time for all flights and the average scheduled turnaround time for all aircraft operated by DL has been counted. At last, the effectiveness and practicability of our method is verified by the flights operation data of the first half of 2018.

Factors influencing charter flight departure delay

This study aims to identify the main factors leading to charter flight departure delay through data mining. The data sample analysed consists of 5484 flights operated by a European airline between 2014 and 2017. The tuned dataset of 33 features was used for modelling departure delay (e.g., if the flight delayed >15 min). The results proved the value of the proposed approach by an area under the receiver operating characteristic curve of 0.831 and supported knowledge extraction through the data-based sensitivity analysis. The features related to previous flight delay information were considered as being the most influential toward current flight being delayed or not, which is consistent with the propagating effect of flight delays. However, it is not the reason for the previous delay nor the delay duration that accounted for the most relevance. Instead, a computed feature indicating if there were two or more registered reasons accounted for 33% of relevance. The contributions include also using a broader data mining approach supported by an extensive data understanding and preparation stage using both proprietary and open access data sources to build a comprehensive dataset.

Restricted Airspace Unit Identification Using Density-Based Spatial Clustering of Applications with Noise

This paper first calculates the departure delay and arrival delay of each flight by mining historical flight data. Then, a new method based on density clustering for identification and visualization of restricted airspace units that considers this activity is proposed. The main objective is to identify the restricted airspace units by calculating the average delay time according to the accumulative delay time of airspace units and the accumulative delay flight. Therefore, the density-based spatial clustering of applications with noise (DBSCAN) clustering method is utilized to match the latitude and longitude coordinates of each spatial domain unit with its delay time to construct a feature matrix, and then clustering analysis is conducted according to the time period. The method aims at identifying the most severe restricted units in each period. The reliability and applicability of the proposed method are validated through a real case study with flight information from Beijing Capital International Airport, Hongqiao International Airport, and Baiyun International Airport during a typical day. The investigation shows that the DBSCAN clustering method can identify the restricted spatial units intuitively on the six flight paths between Beijing Capital International Airport, Hongqiao International Airport, and Baiyun International Airport.

The dynamic programming algorithm for management of real-time aircraft assignments

The schedule is the basis of any airline. In this paper, we provide one of the problems of schedule theory. This problem of optimal management of flight schedule is to minimize flight departure delays and to improve flight on-time performance. This paper provides a conceptual and mathematical formulation of optimizing an operating flight schedule problem. The problem solution is to manage the assignments of specific air-crafts on flights considering the operational information about the implementation of the planned flight schedule. This problem is NP-hard and can not be solved exactly for any real dimensions. We propose the parametric effective algorithm for its approximate solution and provide the statistical data for testing.

The seaport traffic scheduling problem: Formulations and a column-row generation algorithm

Traffic congestion in seaports can lead to uncontrolled execution of berth plans, causing severe vessel delays and long waiting times. In this paper, we schedule the vessel traffic of a seaport by optimizing the utilization of the navigation channel and the anchorage areas in the terminal basin. We model the traffic scheduling problem as a mixed integer linear program (MILP), which takes as inputs the physical layout of a seaport and the berth plans devised by the terminal operators, to minimize the berthing and departure delays of vessels and the number of vessels that cannot berth or depart successfully. We reformulate the MILP into a more compact set-partitioning formulation, develop a column generation algorithm for solving the problem, and propose three performance enhancement strategies, namely, a row generation method, a pricing problem reduction method, and a heuristic pricing method, to accelerate the convergence of the column generation algorithm. Computational performance of the proposed algorithm is evaluated on benchmark instances that are generated from the physical layout and operational data of the Yangshan Deep-water Port in Shanghai.

The Seaport Traffic Scheduling Problem: Formulations and a Column-Row Generation Algorithm

Traffic congestion in seaports can lead to uncontrolled execution of berth plans, causing severe vessel delays and long waiting times. In this paper, we schedule the vessel traffic of a seaport by optimizing the utilization of the navigation channel and the anchorage areas in the terminal basin. We model the traffic scheduling problem as a mixed integer linear program (MILP), which takes as inputs the physical layout of a seaport and the berth plans devised by the terminal operators, to minimize the berthing and departure delays of vessels and the number of vessels that cannot berth or depart successfully. We reformulate the MILP into a more compact set-partitioning formulation, develop a column generation algorithm for solving the problem, and propose three performance enhancement strategies, namely, a row generation method, a pricing problem reduction method, and a heuristic pricing method, to accelerate the convergence of the column generation algorithm. Computational performance of the proposed algorithm is evaluated on benchmark instances that are generated from the physical layout and operational data of the Yangshan Deep-water Port in Shanghai.

Effect of Merger on Market Price and Product Quality: American and US Airways

In this paper, I analyze the effect of the merger between American Airlines (AA) and US Airways (US) on market price and product quality. I use difference-in-differences analysis (DID) as the identification strategy. The DID analysis shows that the price has decreased and that the decrease in price is larger in bigger city-pair markets. Smaller city-pair markets have not benefited from reduction in price. Price has increased in the smaller markets due to the merger. Slot divestiture also has been helpful in reducing the price. The DID analysis also shows that the merger has no significant effect on the frequency of flights or on the number of seats. Delay in arrival and delay in departure have increased, while the merger has a significant effect in reducing the number of canceled flights.

Study of Flight Departure Delay and Causal Factor Using Spatial Analysis

Analysis of flight delay and causal factors is crucial in maintaining airspace efficiency and safety. However, delay samples are not independent since they always show a certain aggregation pattern. Therefore, this study develops a novel spatial analysis approach to explore the delay and causal factors which is able to take dependence and the possible problem involved including error correlation and variable lag effect of causal factors on delay into account. The study first explores the delay aggregation pattern by measuring and quantifying the spatial dependence of delay. The spatial error model (SEM) and spatial lag model (SLM) are then established to solve the error correlation and the variable lag effect, respectively. Results show that the SEM and SLM achieve better fit than ordinary least square (OLS) regression, which indicates the effectiveness of considering dependence by employing spatial analysis. Moreover, the outcomes suggest that, aside from the well-known weather and flow control factors, delay-reduction strategies also need to pay more attention to reducing the impact of delay at the previous airport.

Aircraft turnaround and industrial actions: How ground handlers' strikes affect airport airside operational efficiency

The efficiency of airport turnaround operations has often been compromised by various disruptive events out of the airlines' control, such as strikes, which negatively influence the punctuality and regularity of operations. The purpose of this work is to determine the loss of airport operational performance provoked by ground handlers' industrial actions. A discrete-event simulation model of both aircraft landing-and-takeoff (LTO) cycles and turnaround operations has been built by using AnyLogic. If the number of ground handler's operators decreases, turnaround operations require more time to be performed, resulting in delayed departures and knock-on delays. For the case study of Lisbon “Humberto Delgado” airport, turnaround time increases more than linearly with respect to the decrease of staff resources in service. When the number of operators decreases under a certain threshold, turnaround lengthening cannot be absorbed by buffer times and departure delays propagate in cascade over the day. This threshold should call for emergency actions and contingency plans.

DESIGNING ROUTE DISTRIBUTION USING TWO PHASE TABU SEARCH ON HETEROGENOUS FLEET VEHICLE ROUTING PROBLEM WITH TIME WINDOW IN PT. XYZ TO MINIMIZE TRAVEL DISTANCE

PT. XYZ is a pasteurization milk processing company that produce milk drink from pure cow milk. PT. XYZ don’t sell their product directly to end user, instead they distribute their product to many companies which serve milk for their employees or operators in lunch time. So, their customer is mostly a manufacture company from various kinds of industry. They have about 40 customers and most of them are outside Bandung. However, the delivery may not be done as planned. The average on time delivery is around 96%. it is below PT. XYZ target which is 98%. The impact of the delay itself is vary between customers. Because when delay occur, each customer has their own regulation that has been settled in agreement contract. Based on the delay recapitulation above, there are several factors that caused this problem. Delay in departure is the most influential factors. It is because PT. XYZ don’t have fixed schedule of delivery and they miscalculate the departure time because of improper route determination that also leads to longer travel time. This case is categorized as Vehicle Routing Problem with Heterogeneous Fleet and Time Window (VRPHFTW) that will be solved using one of meta-heuristics algorithm which is Two Phase Tabu Search Algorithm to minimize travel distance. In the end, the travel distance can be minimized 19.48%.