Characterizing the Brazilian airspace structure and air traffic performance via trajectory data analytics

This paper presents a data-driven approach for multi-scale characterization of the Brazilian airspace structure and air traffic operational performance from aircraft tracking data recorded by surveillance systems. Unsupervised learning is performed with a flight trajectory clustering analysis to automatically identify spatial traffic patterns in both the terminal and the en route airspace for major origin-destination pairs of the Brazilian air transportation system. Based on the as-flown route structure learned, quantitative metrics are developed to describe the structural efficiency of the airspace and the operational efficiency of the traffic flows. For this, actual flight trajectories are projected onto reference nominal trajectories in space and time. The results allowed for cross-route comparisons of air traffic flow efficiency across multiple flight phases as well as for the identification of causal factors for trajectory deviations from nominal routes. An interactive data analytics tool is also created to output performance statistics and air traffic visualizations. With the provision of a systematic data-driven approach for characterizing actual air traffic operations, the analytics framework is envisioned to assist airspace design and performance monitoring processes and to provide the basis for developing predictive capabilities in support of traffic flow management.     

A causal factors analysis of aircraft incidents due to radar limitations: The Norway case study

Provision of seamless, safe and effective surveillance services to airspace users requires high performance surveillance sensor coverage in the whole airspace. Limitations in the surveillance system will lead to an inability to provide the required surveillance services to the users. This may result in aircraft incident and accident occurrences. In this paper a case study is developed for the Norwegian airspace, based on five years of safety reports, to identify causal factors of incidents/accidents due to radar system limitations. This is conducted with a safety data analysis from Avinor – Norway's Air Navigation Service Provider (ANSP) and structured communication with Surveillance/ATM safety experts from Avinor. The case study shows that, 76 out of 124 occurrences within the five years in the Norwegian airspace/airport were related to the surveillance function, and 34 out of the 76 occurrences were due to limitations in the radar systems. The analysis identified that the highest contributing causal factors of the occurrences due to radar system limitations were limited surveillance coverage, followed by the lack of situational awareness for flight crew/controllers and unsynchronised surveillance information between flight crew and controllers.     

Berth scheduling by customer service differentiation: A multi-objective approach

In this paper the discrete and dynamic berth allocation problem is formulated as a multi-objective combinatorial optimization problem where vessel service is differentiated upon based on priority agreements. A genetic algorithms based heuristic is developed to solve the resulting problem. A number of numerical experiments showed that the heuristic performed well in solving large, real life instances. The heuristic provided a complete set of solutions that enable terminal operators to evaluate various berth scheduling policies and select the schedule that improves operations and customer satisfaction. The proposed algorithm outperformed a state of the art metaheuristic and provided improved results when compared to the weighted approach.     

Modelling of aircraft rotation in a multiple airport environment

The objective of this paper is to develop a simulation model to simulate aircraft rotation in a multiple airport environment. The developed aircraft rotation model (AR model) consists of two sub-models, namely the aircraft turnaround model, which describes the operation of aircraft turnaround activities at an airport and the Enroute model, which simulates the enroute flight time of an aircraft in the airspace between two airports. Delays due to operational disruptions from aircraft turnaround activities are modelled by stochastic variables in the aircraft turnaround model. Uncertainties from schedule punctuality are modelled by probability density functions in the Enroute model. The proposed aircraft rotation model is employed to carry out a case study by using real schedule and punctuality data from a European schedule airline. Simulation results when compared with observation data validate the effectiveness of the aircraft rotation model. The proposed model is also found suitable for airlines to serve as a schedule planning and analysis tool.     

Freight train scheduling with elastic demand

A train slot selection model based on multicommodity network flow concepts is developed for determining freight train timetables for scheduling rail services along multiple interconnected routes. The model seeks to minimize operating costs incurred by carriers and delays incurred by shippers while ensuring that the schedules and demand levels are mutually consistent. A column generation-based methodology is proposed for train slot selection to meet frequency requirements. This methodology is embedded in a simulation-based iterative framework, where demand for rail services is re-computed in accordance with the train schedule obtained by solving the freight train scheduling problem.     

Impact of operational performance on air carrier cost structure: Evidence from US airlines

The impact of operational performance on airline cost structure is empirically investigated using an aggregate, statistical cost estimation approach. Two distinct sets of operational performance metrics are developed and incorporated into the airline cost models as arguments. Results from estimating a variety of airline cost models reveal that both delay and schedule buffer are important cost drivers. We also find that flight activity outside schedule windows increases cost, whereas flight inactivity within schedule windows does not. Using the estimated cost models, we predict the cost savings to airlines of “perfect” operational performance, obtaining an estimate in the range of $7.1–13.5 billion for 2007.     

Comparing heuristic algorithms of the planar storage location assignment problem

This paper discusses the newly defined planar storage location assignment problem (PSLAP). We develop a mathematical programming model and GA-based and dynamic PSLAP heuristic algorithms for the solving procedure. Using the testing set, we compare the performance of GA-based and dynamic PSLAP heuristic algorithms. The mathematical programming model is utilized as a comparison criterion. The comparison results demonstrate that the dynamic PSLAP heuristic algorithm performs better than the other solving procedures. In addition, we describe simulation experiments conducted to investigate the effects of stock yard layout and production schedule instability on the operation of the block stock yard.     

Dynamic network design for reverse logistics operations under uncertainty

The design of reverse logistics network has attracted growing attention with the stringent pressures from environmental and social requirements. In general, decisions about reverse logistics network configurations are made on a long-term basis and factors influencing such reverse logistics network design may also vary over time. This paper proposes dynamic location and allocation models to cope with such issues. A two-stage stochastic programming model is further developed by which a deterministic model for multiperiod reverse logistics network design can be extended to account for the uncertainties. A solution approach integrating a recently proposed sampling method with a heuristic algorithm is also proposed in this research. A numerical experiment is presented to demonstrate the significance of the developed stochastic model as well as the efficiency of the proposed solution method.     

Towards the optimisation of the schedule reliability of aircraft rotations

A cost minimisation model is developed to optimise the scheduling of aircraft rotation by balancing the use of schedule time, which is designed to control flight punctuality, and delay costs. A case study is conducted using schedule and punctuality data from a European airline. Optimisation shows that the operational performance of an aircraft rotation schedule is improved in terms of: schedule regularity, mean delays and expected delays of aircraft rotation. Although the total schedule time of the study rotation is increased by 5%, a system cost saving of some $9.3 million/1000 aircraft rotations is gained after schedule optimisation. Three schedule reliability surrogates—mean delay time of aircraft rotation, expected delay time of aircraft rotation and schedule regularity—are employed to evaluate the reliability of aircraft rotation schedules. It is found that the reliability and robustness of schedule implementation is significantly improved after optimisation.     

Managing uncertainty in on-demand air travel

Fractional management companies (FMCs) that provide on-demand air travel services experience frequent changes in aircraft availability and flight requests. We propose scheduling heuristics which are both cost-effective and persistent (i.e., close to the original schedule) to address the uncertainty. The heuristics include pro-actively enforcing idleness of aircraft in creating the original schedule, strategically repositioning aircraft to serve yet-unknown demand and dense scheduling. Computational experiments are conducted in a simulator that mimics FMCs’ daily operations. Simulation results quantify the value of each heuristic, which can be easily incorporated into existing computational methods used in FMCs for static scheduling problems.     

Aircraft operational costs and turnaround efficiency at airports

The aim of this paper is to investigate the relationship between flight schedule punctuality and aircraft turnaround efficiency at airports, in order to minimise system operational costs and meanwhile to maintain a required level of schedule punctuality. Investigations of aircraft operational costs, passenger delay costs and airline schedule time-opportunity costs are carried out in this paper. A mathematical model is applied to simulate aircraft turnaround operations by considering the stochastic effects of schedule punctuality as well as aircraft turnaround performance. Two numerical examples demonstrate the performance of the aircraft turnaround model. Results show the significance of a proper use of schedule buffer time in maintaining schedule punctuality performance.     

The optimization model for the location of maritime emergency supplies reserve bases and the configuration of salvage vessels

This paper studies the location–allocation–configuration problem of emergency resources in a maritime emergency system and it proposes a discrete nonlinear integer-programming model, which integrates the location, allocation and the configuration problem. The model is converted into a two-stage model keeping the calculation logic. It designs a hybrid heuristic algorithm and a genetic algorithm. The test results show that the hybrid heuristic algorithm is more efficient than the genetic algorithm, the sensitivity analysis studies the influence of some parameters to the final solution and the Uncertainty–Sensitivity justification tool is used to evaluate the assumptions.     

Mitigation of airspace congestion impact on airline networks

In recent years European airspace has become increasingly congested and airlines can now observe that en-route capacity constraints are the fastest growing source of flight delays. In 2010 this source of delay accounted for 19% of all flight delays in Europe and has been increasing with an average yearly rate of 17% from 2005 to 2010. This paper suggests and evaluates an approach to how disruption management can be combined with flight planning in order to create more proactive handling of the kind of disruptions, which are caused by congested airspace. The approach is evaluated using data from a medium size European carrier and estimates a lower bound saving of several million USD.     

Integrated recovery of aircraft and passengers after airline operation disruption based on a GRASP algorithm

This paper considers the integrated recovery of both aircraft routing and passengers. A mathematical model is proposed based on both the flight connection network and the passenger reassignment relationship. A heuristic based on a GRASP algorithm is adopted to solve the problem. A passenger reassignment solution is demonstrated to be optimal in each iteration for a special case. The effectiveness of the heuristic is illustrated through experiments based on synthetic and real-world datasets. It is shown that the integrated recovery of flights and passengers can decrease both the recovery cost and the number of disrupted passengers.     

Cost-effective pallet management strategies

The existing industry strategies for managing pallets, (single-use expendable pallets, buy/sell programs, and leased pallet pooling programs), are analyzed and compared using push and pull inventory control policies. A two-stage integrated framework is developed that combines cost relationship models with data gathered in industry with multi-echelon inventory performance measures. For the base case, the single-use expendable pallet approach presents the least cost of all strategies, but the leased pallet pooling programs outperform the buy/sell programs in terms of total cost. The intervals where each strategy is most attractive are shown with respect to pallet cost, salvage cost, dwell fees, effective issue fees, retention rates, and transportation costs.     

An empirically grounded agent based simulator for the air traffic management in the SESAR scenario

In this paper we present a simulator allowing to perform policy experiments relative to the air traffic management. Different SESAR solutions can be implemented in the model to see the reaction of the different stakeholders as well as other relevant metrics (delay, safety, etc). The model describes both the strategic phase associated to the planning of the flight trajectories and the tactical modifications occurring in the en-route phase. An implementation of the model is available as an open-source software and is freely accessible by any user.More specifically, different procedures related to business trajectories and free-routing are tested and we illustrate the capabilities of the model on an airspace which implements these concepts. After performing numerical simulations with the model, we show that in a free-routing scenario the controllers perform less operations but the conflicts are dispersed over a larger portion of the airspace. This can potentially increase the complexity of conflict detection and resolution for controllers.In order to investigate this specific aspect, we consider some metrics used to measure traffic complexity. We first show that in non-free-routing situations our simulator deals with complexity in a way similar to what humans would do. This allows us to be confident that the results of our numerical simulations relative to the free-routing can reasonably forecast how human controllers would behave in this new situation. Specifically, our numerical simulations show that most of the complexity metrics decrease with free-routing, while the few metrics which increase are all linked to the flight level changes. This is a non-trivial result since intuitively the complexity should increase with free-routing because of problematic geometries and more dispersed conflicts over the airspace.     

A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling,with consideration of fleet assignment problem

One of the most important airline's products is to determine the aircraft routing and scheduling and fleet assignment. The key input data of this problem is the traffic forecasting and allocation that forecasts traffic on each flight leg. The complexity of this problem is to define the connecting flights when passengers should change the aircraft to reach the final destination. Moreover, as there exists various types of uncertainties during the flights, finding a solution which is able to absorb these uncertainties is invaluable. In this paper, a new robust mixed integer mathematical model for the integrated aircraft routing and scheduling, with consideration of fleet assignment problem is proposed. Then to find good solutions for large-scale problems in a rational amount of time, a heuristic algorithm based on the Simulated Annealing (SA) is introduced. In addition, some examples are randomly generated and the proposed heuristic algorithm is validated by comparing the results with the optimum solutions. The effects of robust vs non-robust solutions are examined, and finally, a hybrid algorithm is generated which results in more effective solution in comparison with SA, and Particle Swarm Optimization (PSO).     

Air-traffic complexity resolution in multi-sector planning

This paper considers the problem of minimizing the traffic complexities in an airspace of adjacent sectors. The traffic complexity of a sector is determined by the numbers of flights within it, near its border, and on non-level segments within it. The dimensions of complexity resolution involve changing the take-off times of non-airborne flights, changing the approach times into the chosen airspace of airborne flights by slowing and accelerating within the two layers of feeder sectors around that airspace, as well as changing the altitude at way-points in that airspace. Experiments with European flight profiles from the Central Flow Management Unit show that these forms of resolution can lead to significant complexity reductions and rebalancing.     

A heuristic approach to logistics network design for end-of-lease computer products recovery

This paper discusses the logistics network design for end-of-lease computer products recovery by developing a deterministic programming model for systematically managing forward and reverse logistics flows. Due to the complexity of such network design problem, a two-stage heuristic approach is developed to decompose the integrated design of the distribution networks into a location–allocation problem and a revised network flow problem. The applicability of the proposed method is illustrated in a numerical study. Computational experiments demonstrate that high-quality solutions are obtained while modest computational overheads are incurred.     

A short-term flight scheduling model for international express package delivery

A short-term flight scheduling model for air express carriers is developed to determine suitable routes and flight schedules with the objective of minimizing operating costs, subject to related operating constraints. The model is formulated as an integer multiple commodity network flow problem solved using mathematical programming. For evaluation, a case study is used based on the operating data from a major international air express carrier.