Airline Scheduling Research Articles

A benders decomposition approach for an integrated airline schedule design and fleet assignment problem with flight retiming, schedule balance, and demand recapture

The airline’s ability to offer flight schedules that provide service to passengers at desired times in competitive markets, while matching demand with an aircraft fleet of suitable size and composition, can significantly impact its profits. In this spirit, optional flight legs can be considered to construct a profitable schedule by optimally selecting among such alternatives in concert with assigning the available aircraft fleet to all the scheduled legs. Examining itinerary-based demands as well as multiple fare-classes can effectively capture network effects and realistic demand patterns. In addition, allowing flexibility on the departure times of scheduled flight legs can increase connection opportunities for passengers, hence yielding robust schedules while saving fleet assignment costs within the framework of an integrated model. Airlines can also capture an adequate market share by balancing flight schedules throughout the day, and recapture considerations can contribute to more realistic accepted demand realizations. We therefore propose in this paper a model that integrates the schedule design and fleet assignment processes while considering flexible flight times, schedule balance, and recapture issues, along with optional legs, path/itinerary-based demands, and multiple fare-classes. A polyhedral analysis is conducted to generate several classes of valid inequalities, which are used along with suitable separation routines to tighten the model representation. Solution approaches are designed by applying Benders decomposition method to the resulting tightened model, and computational results are presented using real data obtained from United Airlines to demonstrate the efficacy of the proposed procedures.

Visitor and Resident Images of Qingdao, China, as a Tourism Destination

This article compares the images of Qingdao, China, as perceived by visitors and residents and examines whether these images are affected by information sources, age, education, and place attachment. The data were collected using a self-administered survey of 578 visitors and 337 residents of Qingdao throughout June and July of 2009. The image construct was conceptualized into two dimensions: cognitive and affective. It was found that the images perceived by visitors and residents converged primarily on cognitive images and less so on affective images. The results of a Mann-Whitney U test reveal that the main differences between the images held by visitors and residents are in 10 cognitive images (seafood, cultural attraction, highway system, traffic congestion, airline schedules, local people, beaches, weather, scenery, and hygiene and cleanliness) and in two affective images (arousing–sleepy and exciting–gloomy). Spearman's rank correlation test revealed that there is a weak positive correlation between place attachment and the images of Qingdao perceived by both visitors and residents. Age, education, and information sources are only partially correlated with visitor and resident images, with weak correlations.

Commonwealth of the Northern Mariana Islands

Commonwealth of the Northern Mariana Islands Samuel F. McPhetres (bio) Commonwealth of the Northern Mariana Islands The year in review was again one of shock and awe with major crises being confronted with regard to the Retirement Fund, budget process, Commonwealth Utilities Corporation, and US-CNMI relations. Economic development has been sporadic at best. This year's report continues in the vein of previous reports. President Obama's American Reconstruction and Recovery Act resulted in approximately $94 million being directed toward the commonwealth. Some of that has already been applied to road construction, school repairs, and a variety of other projects. This spending has yet to result in any tangible improvements in day-to-day [End Page 190] living, however. Gas prices have continued to fluctuate. As of May 2010 regular gas was around $3.90 a gallon on Saipan and over $5.00 a gallon on Rota. The minimum wage increased by fifty cents last November to $4.55, but another fifty-cent increase, to $5.05, has been delayed until September 2010. One of the problems handicapping planning in the commonwealth has been the issue of demographics. Since the last census in 2000, when the total population of the commonwealth was pegged at about 70,000 (approximately 40,000 were guest workers), the garment industry has closed down and the economic conditions have driven many local people off island. There has been no way to accurately estimate what the population is at this point. Working estimates go from a low of 50,000 to a high of 60,000. The decennial census, which is taking place as this is being written, will go a long way toward resolving this problem and provide for more rational planning at all levels. In the area of development, as reported last year (McPhetres 2010), two new hotels signed land leases for major investment programs. The NeoGold Wings Casino and Spa on Tinian and the Flame Sako project in the Marpi Area of northern Saipan were promoted as major investments totaling hundreds of millions of dollars. To date, beyond getting their leases approved by the legislature, no progress has been made on either project. However, in May 2010 the Korean investment company on the Flame Sako project did pay their overdue lease payments and promised that they would be going ahead with the resort development. As of this writing, there has been no movement on the part of the Neo-Gold Wings company to pay their outstanding lease rent. Airline scheduling continued to be a problem, with only intermittent flights arriving from Japan. Only Northwest Airlines had regularly scheduled daily flights between Saipan and Japan. Regularly scheduled flights did come from Korea, which also ferried in Russian and Chinese tourists. Tourism was still way down, partially because of changes in immigration policies following the federalization of immigration in November 2008. This has caused confusion about impending visa regulations. The implementation of the Covenant Implementation Act (Public Law 110-229), which is commonly seen as the US takeover of immigration in the commonwealth, has resulted in a great deal of confusion and worry in several sectors. The Department of Homeland Security has yet to finalize many of the regulations it is responsible for in the commonwealth while at the same time the US Congress is now facing a major challenge in reforming national immigration laws. Pressure is on Congress to grant special immigration status to persons who have lived legally in the Marianas for five years or longer. The secretary of the interior recommended that these alien workers be allowed to adjust their status and suggested that there are five options under current US law that could be applied: An alien worker could be granted (1) citizenship by act of Congress; (2) permanent residence status (ie, a green card) with a pathway to citizenship through a five-year residence anywhere in the United States or [End Page 191] its territories; (3) permanent resident status leading to US citizenship after a five-year minimum residence in the commonwealth; (4) non-immigrant status similar to that negotiated for citizens of the freely associated states, whereby such persons may live and work in the United States and...

Uncertainty feature optimization: An implicit paradigm for problems with noisy data

AbstractOptimization problems with noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the uncertainty set and suffer from an erroneous estimation of the noise.In this article, we introduce a framework that considers the uncertain data implicitly. We define the concept of Uncertainty Features (UF), which are problem‐specific structural properties of a solution. We show how to formulate an uncertain problem using the Uncertainty Feature Optimization (UFO) framework as a multi‐objective problem. We show that stochastic programming and robust optimization are particular cases of the UFO framework. We present computational results for the Multi‐Dimensional Knapsack Problem (MDKP) and discuss the application of the framework to the airline scheduling problem. © 2011 Wiley Periodicals, Inc. NETWORKS, 2011

The airline schedule optimization model: validation and sensitivity analysis

The Airline Schedule Optimization (ASO) Advanced decision support system (DSS) provides a solution as a proposal of a new flight schedule, in situations when an airline's flight scheduled is disturbed, which would minimize the negative effects of those disturbances. The ASO DSS was successfully tested and validated in Airline Operation Control Centre. Further, the sensitivity analysis was done where the main task was to analyze how the values of the penalties defined in the DSS influence on generated solutions by the ASO Advanced. The results of the model validation as well as the sensitivity analysis are presented in this paper.

Integrated Robust Airline Schedule Development

In air transportation, airline profitability is influenced by the airline's ability to build flight schedules. In order to generate operational schedules, airlines engage in a complex decision-making process, referred to as airline schedule planning. Up to now, the generation of flight schedules has been separated and optimized sequentially. The schedule design has been traditionally decomposed into two sequential steps. The frequency planning and the timetable development. The purpose of the second problem of schedule development, fleet assignment, is to assign available aircraft types to flight legs such that seating capacity on an assigned aircraft matches closely with flight demand and such that costs are minimized. Our work integrates these planning phases into one single model in order to produce more economical solutions and create fewer incompatibilities between the decisions. We propose an integrated robust approach for the schedule development step. We design the timetable ensuring that enough time is available to perform passengers’ flight connections, making the system robust avoiding misconnected passengers. An application of the model for a simplified IBERIA network is shown.

Fast Algorithms for Specially Structured Minimum Cost Flow Problems with Applications

The objective of the classical minimum cost flow problem is to send units of a good that reside at one or more points in a network (sources or supply nodes) with arc capacities to one or more other points in the network (sinks or demand nodes), incurring minimum cost. We develop fast algorithms for previously unstudied specially structured minimum cost flow problems that have applications in many areas, such as locomotive and airline scheduling, repositioning of empty rail freight cars, highway and river transportation, congestion pricing, shop loading, and production planning. First, we consider the case where the n1 supply and n2 demand nodes lie on a circle (or line) (n = n1 + n2) and flow is allowed only in one direction; our algorithm solves this problem in O(n) time. Next, we consider a constrained version of this problem and show that it can be solved in O(n log n2) time. Finally, we consider the version where the nodes lie on a circle (or line), flow is allowed in both directions, and the costs of flow between two nodes in the clockwise and the counterclockwise direction are different; our algorithm solves this problem in O(n log n) time. Our algorithms are based on the successive shortest-path algorithm for the minimum cost flow problem. We exploit the special structure of the problem and use advanced data structures, when required, to achieve short run times.

Study on Optimization of Multi-Type Aircraft Scheduling Robust Model

Phased implementation approach, namely three models: aircraft type distribution model, aircraft scheduling model, robustness model is used to achieve the optimization of aircraft scheduling robustness. Aircraft type distribution model is established to obtain the best model of each leg; then fleet scheduling model is established to determine specified type in the implementation of the specific aircrafts for each flight, flight strings, which meet the constraints, are obtained by solving; finally, the flight robustness model is established, that is, flight string with minimal impact is selected from above flight strings to obtain high robustness of multi-type flight scheduling combination. The phased multi-type aircraft scheduling robust model has been successfully applied in the domestic airline scheduling, it has been achieved a better effect of robust optimization.

Integrated Airline Schedule Design and Fleet Assignment: Polyhedral Analysis and Benders' Decomposition Approach

The main airline operations consist of schedule planning, fleet assignment, aircraft routing, and crew scheduling. To improve profitability, we present in this paper an integrated fleet assignment model with schedule planning by simultaneously considering optional flight legs to select along with the assignment of aircraft types to all scheduled legs. In addition, we consider itinerary-based demands for multiple fare classes. A polyhedral analysis is conducted of the proposed mixed-integer programming model to tighten its representation via several classes of valid inequalities. Solution approaches are developed by applying Benders' decomposition method to the resulting lifted model, and computational results are presented using real data obtained from a major U.S. airline to demonstrate the efficacy of the proposed procedures.

Understanding the relationship between price, revenue management controls and scheduled capacity – A price balance statistic for optimizing pricing strategies

The relationship among pricing, revenue management (RM) controls and capacity directly impacts the profitability potential of an airline's schedule. Too much capacity in a market leads to wide open RM controls with deeply discounted prices to stimulate demand to fill the available seats at unprofitable yields. On the other hand, a schedule that does not supply enough capacity can lead to higher prices and stringent controls that invite competition. Understanding the relationship between the scheduled capacity, pricing structure and RM controls gives an airline the opportunity to better align scheduled capacity, adjust pricing structures and manage the seat inventory to maximize profitability. This article provides a practical approach to understanding the impact of scheduled capacity and pricing structures on overall network revenue. A macro-level metric known as the ‘price balance statistic’ is described for evaluating the quality of a given pricing strategy and guiding a search algorithm to identify an optimal alignment between pricing structure, scheduled capacity and RM controls using marginal revenue principles.

Sensitivity analysis of airline schedule optimization (ASO) advanced model

The ASO model provides a proposal for a new flight schedule, in situations when a carrier’s flight scheduled is disrupted, and which would minimize the negative effects of the disruption. The objective function of the model is a mathematical formulation of the company’s goals and preferences, where all assumptions and operational constraints must be satisfied. The disruption costs are given in weighted coefficients which present the penalties that can be changed by the dispatcher. One of the goals was to test to what degree the generated solutions are sensitive to changes in penalty values.

Simultaneous recovery model for aircraft and passengers

Usually some unforeseen events make airlines to reconstruct their schedules. A mathematical model for airlines schedule recovery which recovers aircrafts and disrupted passengers simultaneously is presented in this study. Aircraft recovery decisions affect on passengers but disrupted passengers and recovering them were not explicitly considered in the most previous aircraft recovery models so recovery of these two resources – aircrafts and passengers – concurrently is one of our contributions. The modeling is based on defining the recovery scope as well as employing aircraft rotations and passengers’ itineraries instead of flights. These are two of our other contributions. Our model examines possible flight re-timing, aircraft swapping, ferrying, utilization of reserve aircrafts, cancellation, and passenger reassignment to generate an efficient schedule recovery plan. Model parameters are user-specific therefore it helps airlines to apply their policies in the model. Defining the recovery scope reduces the problem size and ensures that the schedule returns to normal within a certain time. The objective is in the form of cost minimization which involves three kinds of cost—operational aircraft recovery, flight cancellation, and delay as well as disrupted passengers. A data set with two disruption scenarios is used to test the proposed model. The computational results show that it is capable of handling the simultaneous aircraft and passenger recovery problem successfully.

Heuristic approach to the airline schedule disturbances problem

When disturbances make it impossible to realise the planned flight schedule, the dispatcher at the airline operational centre defines a new flight schedule based on airline policy, in order to reduce the negative effects of these perturbations. Depending on airline policy, when designing the new flight schedule, the dispatcher delays or cancels some flights and reassigns some flights to available aircraft. In this paper, a decision support system (DSS) for solving the airline schedule disturbances problem is developed aiming to assist decision makers in handling disturbances in real-time. The system is based on a heuristic algorithm, which generates a list of different feasible schedules ordered according to the value of an objective function. The dispatcher can thus select and implement one of them. In this paper, the possibilities of DSS are illustrated by real numerical examples that concern JAT Airways' flight schedule disturbances.

The airline perturbation problem: considering disrupted passengers

When airlines are faced with some unforeseen short-term events, they have to reconstruct their flight schedules. Although aircraft recovery decisions affect passengers, these disrupted passengers and recovering them have not been explicitly considered in most previous aircraft recovery models. This paper presents an assignment model for airline schedule recovery which recovers both aircraft and disrupted passengers simultaneously, using a rolling horizon time framework. Our model examines possible flight retiming, aircraft swapping, over-flying, ferrying, utilization of reserve aircraft, cancellation and passenger reassignment to generate an efficient schedule recovery plan. The model ensures that the schedule returns to normal within a certain time and the objective is to minimize operational recovery aircraft cost, cancellation and delay cost as well as disrupted passenger cost. The model is tested using a data-set with two disruption scenarios. The computational results show that it is capable of handling the integrated aircraft and passenger recovery problem successfully.

Modeling Framework for Evaluating Sensitivity of Airline Schedules to Airport Congestion Pricing

This paper presents a modeling framework for evaluating the sensitivity of airline schedules to the congestion pricing of airports. The framework allows airport agencies and aviation management authorities to examine the effectiveness of airport pricing schemes in reducing flight delays at congested airports. The framework replicates airlines' schedule planning decisions in a free market as it considers the effect of applying time-varying landing fees and associated delay externalities. The framework adopts the concept of Wardrop's network equilibrium as the basis for modeling competition among air carriers. A hypothetical airline network with two competing air carriers is used to illustrate the capabilities of the developed framework. The results of the conducted experiments show the importance of considering the network effect in developing effective pricing strategies.

Congested hubs

Hub congestion is a major concern and a relevant policy issue because it causes important problems at airports such as flight delays, cancellations and missed connections that end up affecting both air travelers and airlines. We address the interplay between flight frequency and aircraft size in a congestion-pricing model, finding that airlines schedule too many flights using overly small aircraft, which constitutes a major contributor to congestion. Then we work out the needed congestion tolls, which account for the congestion imposed on other carriers and the congestion imposed on all passengers. Finally, we analyze the effects on congestion of network size, airport capacity, alliances and competition in layover time.

Constraint-specific recovery network for solving airline recovery problems

In this paper, we consider the recovery of an airline schedule after an unforeseen event called disruption, making the planned schedule infeasible. We present a modeling framework that allows the consideration of operational constraints within a Column Generation (CG) scheme. We introduce the general concept of recovery network, generated for each individual unit of the problem, and show how unit-specific constraints are modeled using resources. We fully illustrate the concept by solving the Aircraft Recovery Problem (ARP) with maintenance planning, we give some insights into applying the model to the Passenger Recovery Problem (PRP) and we present computational results on real data.

How the presence of low-cost carrier competition scheduling differentiation

This study explores the relation between airline market structure and schedule differentiation. Using a location theory framework applied to product differentiation over the time scale, the analysis relates the level of competition, and the presence of low-cost carriers in non-stop US markets to schedule clustering. As expected from theory, it is found that schedule clustering increases with competition, resulting in reduction in product differentiation. It is also found that this tendency is lower in the presence of low-cost carriers and when there is a strong hub effect where dominant hub airline own, rather than compete with their feeder subsidiaries.

Disruption management in the airline industry—Concepts, models and methods

This paper provides a thorough review of the current state-of-the-art within airline disruption management of resources, including aircraft, crew, passenger and integrated recovery. An overview of model formulations of the aircraft and crew scheduling problems is presented in order to emphasize similarities between solution approaches applied to the planning and recovery problems. A brief overview of research within schedule robustness in airline scheduling is included in the review, since this proactive measure is a natural complement to disruption management.

A multi-objective approach for robust airline scheduling

We present a memetic approach for multi-objective improvement of robustness influencing features (called robustness objectives) in airline schedules. Improvement of the objectives is obtained by simultaneous flight retiming and aircraft rerouting, subject to a fixed fleet assignment. Approximations of the Pareto optimal front are obtained by applying a multi-meme memetic algorithm. We investigate biased meme selection to encourage exploration of the boundaries of the search space and compare it with random meme selection. An external population of high quality solutions is maintained using the adaptive grid archiving algorithm. The presented approach is applied to investigate simultaneous improvement of reliability and flexibility in real world schedules from KLM Royal Dutch Airlines. Experimental results show that the approach enables us to obtain schedules with significant improvements for the considered objectives. A large scale simulation study was undertaken to quantify the influence of the robustness objectives on the operational performance of the schedules. Rigorous sensitivity analysis of the results shows that the influence of the schedule reliability is dominant and that increased schedule flexibility could improve the operational performance.