An optimization approach to aircraft dispatching strategy with maintenance cost – A case study

This paper presents an optimization approach to identify aircraft dispatching strategy at a flight training school. The strategy adopted by the school was to dispatch the aircraft which is closest to its scheduled maintenance. This strategy was examined and compared with other potential dispatching strategies. The paper presents a mixed integer linear programming model to identify the strategy that minimizes the total cost of scheduled maintenance. The analysis shows that the optimization approach can save 2%–5% on annual maintenance cost compared with other strategies. The model can equally be applied to rental cars or trucking companies.     

Scheduling aircraft take-offs and landings on interdependent and heterogeneous runways

This paper presents an optimization method for the aircraft scheduling problem with general runway configurations. Take-offs and landings have to be assigned to a runway and a time while meeting the sequence-dependent separation requirements and minimizing the costs incurred by delays. Some runways can be used only for take-offs, landings, or certain types of aircraft while schedules for interdependent runways have to consider additional diagonal separation constraints.Our dynamic programming approach solves realistic problem instances to optimality within short computation times. In addition, we propose a rolling planning horizon heuristic for large instances that returns close-to-optimal results.     

Tactical crew planning in railways

Tactical crew capacity planning problem in railways involves finding the minimum number of crews in a region required to operate a predetermined set of train duties satisfying the strict day-off requirement for crew. For the single-region problem, we develop two solution approaches based on a space–time network representation: the sequential approach and the integrated approach. We also study the multi-regional capacity planning problem where we minimize total system-wide capacity by simultaneously considering multiple regions within a neighborhood search algorithm based on our solution methods for the single-region problem. We present the computational study on problem instances from Turkish State Railways.     

Aircraft routing under different business processes

Given a set of scheduled flights that must be operated by the same aircraft type, the aircraft routing problem consists of building anonymous aircraft routes that respect maintenance requirements and cover each flight exactly once. This paper looks at the nature of the problem and introduces a classification according to three business processes that are used to assign the anonymous routes to the specific aircraft tail numbers. Furthermore, we compare the aircraft routing problem variants resulting from these three processes with regard to their adaptability to different contexts, the difficulty of solving them, the cost of the computed solutions, and the robustness of these solutions.     

An explainable machine learning approach to improve take-off time predictions

Accurate aircraft trajectory predictions are necessary to compute exact traffic demand figures, which are crucial for an efficient and effective air traffic flow and capacity management. At present, the uncertainty of the take-off time is one of the major contributions to the loss of trajectory predictability. In the EUROCONTROL Maastricht Upper Area Control Centre, the predicted take-off time for each individual flight relies on the information received from the Enhanced Traffic Flow Management System. However, aircraft do not always take-off at the times reported by this system due to several factors, which effects and interactions are too complex to be expressed with hard-coded rules. Previous work proposed a machine learning model that, based on historical data, was able to predict the take-off time of individual flights from a set of input features that effectively captures some of these elements. The model demonstrated to reduce by 30% the take-off time prediction errors of the current system one hour before the time that flight is scheduled to depart from the parking position. This paper presents an extension of the model, which overcomes this look-ahead time constraint and allows to improve take-off time predictions as early as the initial flight plan is received. In addition, a subset of the original set of input features has been meticulously selected to facilitate the implementation of the solution in an operational air traffic flow and capacity management system, while minimising the loss of predictive power. Finally, the importance and interactions of the input features are thoroughly analysed with additive feature attribution methods.     

A qualitative study of outsourced aeronautical maintenance: The case of Brazilian organizations

The outsourcing of aeronautical maintenance has been criticized for the quality of services offered. According to the literature, airlines have contracted repair stations to perform maintenance activities on their aircraft or parts when attempting to optimize resources (time, facilities, personnel, money). The attempt to reduce costs in maintenance activities and regulatory deficiencies can lead to maintenance management practices that could threaten equipment airworthiness. Therefore, the aim of this research was to evaluate whether outsourced aeronautical maintenance is aligned to common industrial maintenance management practices. To achieve this goal, qualitative exploratory research was conducted on Brazilian repair stations. For data collection, a questionnaire was developed based on seven factors related to aircraft maintenance. The data revealed that a mismatch exists between the best maintenance management practices and expected repair station performance.     

A novel heuristic approach for solving aircraft landing problem with single runway

Nowadays, airlines administrations are more willing to utilize optimization tools to control air traffic due to considerable increases in volume of air transports. A challenging problem in the field of air traffic is how to optimally schedule landing time of aircrafts and assign them to different runways such that early and late landing costs are minimized. This problem is called aircraft landing problem (ALP). This paper proposes a novel decomposition based heuristic by solving two sub-problems for the ALP with single runway. In the first sub-problem, we apply the adaptive large neighborhood search (ALNS) algorithm to find a sequence of aircrafts. The solution found in the first sub-problem will be sent to the second sub-problem, to check for the feasibility of the solution using CPLEX solver. A set of benchmark problem are taken from the OR library for the purpose of comparison with other existing approaches. The computational results exhibit that the proposed algorithm is capable of finding the best known optimal solution for all the instances.     

A qualitative study on the exploration of challenges to the implementation of the Safety Management System in aircraft maintenance organizations in Turkey

Safety management has recently started using a paradigm that ‘sees the world as it is’ rather than ‘prescribing how it should be’. The Safety Management System (SMS), a product of this paradigm shift, has fairly new and different characteristics. These changes are expected to pose a number of challenges to the successful implementation of the SMS. This qualitative research study sets out to explore challenges to the implementation of the SMS in aircraft maintenance organizations in Turkey, with reference to the perceptions of Quality Management Systems (QMSs) and SMS experts working at these maintenance organizations.Qualitative data was collected from thirty participants through an open-ended questionnaire. Both inductive and deductive methods were used for the data analysis. The results suggest that the SMS entails a cultural transformation and is likely to bring about certain challenges because of its new and different characteristics. It is concluded that significant challenges may derive from a poor positive safety culture. Top management support and the practices of the civil aviation authority also have the potential to pose challenges. Other challenges are expected to result from SMS training and the need for the integration of stakeholder SMSs.The research results are expected to improve the success of the SMS and hence safety in aircraft maintenance. The results may also encourage the regulatory authorities to take measures to improve the success of the SMS in the launch of State Safety Programs (SSPs).     

The geography of freighter aircraft operations in the Pacific Basin

The expansion of scheduled freighter aircraft operations is a prominent feature of the contemporary international airline industry. By 2000, more than 1600 freighter aircraft were in use worldwide, with much of that capacity deployed on routes in the Pacific Basin. This paper evaluates the factors that shape the geography of scheduled freighter aircraft operations with particular attention given to the place of individual Asian cities within that geography. The paper also examines the separate spatial strategies exhibited by the scheduled freighter operations of two important categories of cargo airlines: the express carriers like FedEx and the combination carriers like Lufthansa.     

Scheduling technicians for planned maintenance of geographically distributed equipment

A real-world planned maintenance scheduling problem that exists at several business units within United Technologies Corporation (UTC) is addressed in this paper. The scheduling problem is formulated as a multiple tour maximum collection problem with time-dependent rewards and an adaptive memory tabu search heuristic is developed to solve it. The effectiveness of the proposed solution approach is examined using real-world problem instances supplied by UTC. Relevant upper bounds are derived for the application. Results of numerical experiments indicate that the proposed tabu search heuristic is able to obtain near optimal solutions for large-size (i.e., actual) problem instances in reasonable computation time.     

The congested multicommodity network design problem

This paper studies a version of the fixed-charge multicommodity network design problem where in addition to the traditional costs of flow and design, congestion at nodes is explicitly considered. The problem is initially modeled as a nonlinear integer programming formulation and two solution approaches are proposed: (i) a reformulation of the problem as a mixed integer second order cone program to optimally solve the problem for small to medium scale problem instances, and (ii) an evolutionary algorithm using elements of iterated local search and scatter search to provide upper bounds. Extensive computational results on new benchmark problem instances and on real case data are presented.     

Truck and trailer scheduling in a real world,dynamic and heterogeneous context

We present a new variant of the Vehicle Routing Problem based on a real industrial scenario. This VRP is dynamic and heavily constrained and uses time-windows, a heterogeneous vehicle fleet and multiple types of job. A constructive solver is developed and tested using dynamic simulation of real-world data from a leading Scottish haulier. Our experiments establish the efficiency and reliability of the method for this problem. Additionally, a methodology for evaluating policy changes through simulation is presented, showing that our technique supports operations and management. We establish that fleet size can be reduced or more jobs handled by the company.     

Management of airport congestion through slot allocation

The lack of airport slots (the time allocated for an aircraft to land or take off), particularly at airports which experience congestion, have reached unmanageable proportions in recent years. The International Civil Aviation Organization (ICAO) records that, by the end of 1997, there were 132 slot controlled international airports. The World of Civil Aviation, 1997–2000. ICAO Circular 273-AT/113, p. 12 (118 year round and 14 during peak seasons). Between 1989 and 1998 the reported number of commercial aircraft in service increased by about 60% from 11,253 to 18,139 aircraft. In 1998, 1463 jet aircraft were ordered, compared with 1309 in 1997, and 929 were delivered compared with 674 aircraft in 1997. In 1998, the total scheduled traffic carried by airlines of the 185 Contracting States of ICAO amounted to a total of about 1462 million passengers and about 26 million tonnes of freight. These figures¹ are reflective of the rapidly increasing frequency of aircraft movements at airports, calling for drastic management of airport capacity. To cope with the demand, airlines are forming strategic alliances with themselves by utilizing such commercial tools as franchising, leasing and interchange of aircraft. The management of airport capacity through slot allocation is a critical consideration for the world aviation community. This article analyses the problem and discusses various issues related thereto.     

A dynamic approach for aircraft assignment and maintenance scheduling by airlines

The problems of assigning planes to flights and of fleet maintenance operations scheduling are considered in this paper. While recent approaches make use of artificial intelligence techniques running on main frame computers to solve combinatorial optimization problems for nominal operations, a dynamic approach is proposed here to face on-line operation conditions. The proposed solution mixes a Dynamic Programming approach (to cope with the fleet assignment problem) and a heuristic technique (to solve the embedded maintenance schedule problem). When applied to a medium charter airline, this approach shows acceptability characteristics for operational staffs, while providing efficient solutions. The proposed solution scheme can be considered as the basis for the development of an on-line decision support system for fleet operations management within airlines.     

Runway capacity management – An empirical study with application to Doha International Airport

This paper examines a three-faceted approach for runway capacity management, based on the runway configuration, a chosen scheduling approach, and an aircraft separation standard. These factors prompt alternative runway settings that are encapsulated using a classical mixed-integer formulation. The optimal solution for each runway setting is compared against our proposed optimization-based heuristic. This integrated approach is applied to investigating the transition from the (Old) Doha International Airport to the New Doha International Airport. Our empirical study based on historical data reveals that the proposed heuristic consistently yields optimal or near-optimal schedules, with considerable savings in fuel cost and reductions in delays, while preserving the spirit of an FCFS sequencing policy.     

Efficient aircraft spare parts inventory management under demand uncertainty

In airline industries, the aircraft maintenance cost takes up about 13% of the total operating cost. It can be reduced by a good planning. Spare parts inventories exist to serve the maintenance planning. Compared with commonly used reorder point system (ROP) and forecasting methods which only consider historical data, this paper presents two non-linear programming models which predict impending demands based on installed parts failure distribution. The optimal order time and order quantity can be found by minimizing total cost. The first basic mathematical model assumes shortage period starts from mean time to failure (MTTF). An iteration method and GAMS are used to solve this model. The second improved mathematical model takes into account accurate shortage time. Due to its complexity, only GAMS is applied in solution methodology. Both models can be proved effective in cost reduction through revised numerical examples and their results. Comparisons of the two models are also discussed.     

An exact solution approach for vehicle routing and scheduling problems with soft time windows

A new column generation based exact optimization approach for the vehicle routing and scheduling problem with semi soft time windows (VRPSSTW) is presented. Elementary shortest path problem with resource constraints and late arrival penalties is solved as a subproblem, which rises from the Dantzig–Wolfe decomposition method. Exact solutions of VRPSSTW and hard time windows variant are compared on Solomon’s benchmark instances as well as on an instance based on Tokyo road network. It was found that the VRPSSTW solution results in fewer routes thus overall costs are reduced and late arrival penalties contribute only a small fraction to total cost.     

Aircraft and passenger recovery during an aircraft’s unexpected unavailability

Airlines design their initial schedules under the assumption that all resources will be available on time and flights will operate as planned. However, some disruptions occur due to mechanical failures and unexpected delays of maintenance, making the aircraft unavailable for a certain period of time. These deviations from the initial plan result in high operational costs in addition to the serious inconveniences experienced by passengers. In order to handle aircraft and passenger recovery problems simultaneously, we work on integrated networks at which aircraft routings and passenger itineraries are superimposed. Consequently, we could calculate the actual profit and cancellation cost by evaluating each passenger itinerary while considering the seat capacity limitations. In our computational results, we use a daily schedule of a major U.S. airline and clearly demonstrate that there is an optimal trade-off between operating and passenger-related costs.     

A matheuristic approach to the air-cargo recovery problem under demand disruption

Air cargo transport is subject to unpredictable changes in expected demand, necessitating adjustments to itinerary planning to recover from such disruptions. We study a flight rescheduling problem to react to cargo demand disruptions in the short run. To increase flexibility, we consider two different cargo assignment policies. We propose a matheuristic approach to solve the problem that provides high-quality solutions in a short computational time, based on column generation in which each subproblem is solved using an ad-hoc heuristic. The approach is tested on demand disruption instances containing up to 75 air cargo orders with different penalty levels. The results show that the proposed method improves profit by 54% over the solution generated by a commercial MIP solver within a 1-h time limit, and by 15% over the solution with the routes fixed as in the original flight planning that only allows cargo to be re-routed. We also show that there exist incremental benefits in the range of 3–5% by allowing cargo for a given order to be transported by various aircraft.     

Criteria selection and multi-objective optimization of aircraft landing problem

Inspired by the similarities of the aircraft landing problem (ALP) and the single machine scheduling problem, we propose a criteria selection method that has been used successfully in the single machine scheduling problem to determine appropriate objective functions of ALP. First, for four different types of criteria—min-max, min-sum, completion time related, and due-dates related criteria—their corresponding physical meanings in ALP are elaborated. Then, a criteria selection method is proposed to determine several appropriate criteria, which are taken as the multi-objective while modeling ALP. Different solution algorithms, including Imperialist Competitive Algorithm (ICA), are adopted to solve the multi-objective ALP. Finally, the performance of the proposed model and method are evaluated using a set of benchmark instances. The computational results demonstrate the efficiency of our approach for solving ALP, which can simultaneously improve punctual performance, enhance runway utilization, reduce air traffic controller workload, and maintain equity among airlines.