Automated Disruption Assistance

During the last decade, commercial aviation in Brazil has grown significantly, overcoming the number of 100 million passengers per year. The intense operation represents a challenge for the air carriers, especially during flight disruptions. In Brazil, besides the re-accommodation of the passengers into other flights, under certain circumstances, the ANAC 400 resolution requires the airlines to provide a series of material assistance. Meal, transport, and hotel make part of the exigences stated by the ANAC 400. Our study aims to analyze the current process that is mainly manual and propose to automatize several steps through a self-service solution. The researchers verified the potential adoption of the solution through a survey where the great majority of respondents are favorable for using self-services and avoid lines at the airport. The researchers also created a financial analysis to demonstrates the benefits of the solution through the reduction of headcount to execute the process

Using Ground Transportation for Aviation System Disruption Alleviation

An investigation was made into whether passenger delays and airline costs due to disruptive events affecting European airports could be reduced by a coordinated strategy of using alternative flights and ground transportation to help stranded passengers reach their final destination using airport collaborative decision-making concepts. Optimizing for airline cost for hypothetical disruptive events suggests that, for airport closures of up to 10 h, airlines could benefit from up to a 20% reduction in passenger delay-related costs. The mean passenger delay could be reduced by up to 70%, mainly via a reduction in very long delays

Dynamic passenger recovery model for airline disruption management

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 UniversityAirline operations experience schedule disruptions every day. These schedule disruptions require intervention from the airline operations controllers through schedule recovery. In a hub and spoke airline network model, a disruption such as a flight cancellation can affect passenger itineraries in multiple fight legs, making it hard for airlines to re-accommodate disrupted passengers within a short time period. The current airline recovery solutions do not explicitly consider passenger recovery. This dissertation investigates the passenger recovery process by considering the challenges faced by passengers during a schedule disruption, the current solutions used to recover disrupted passengers and how a suitable solution can be designed, developed, tested and validated to ensure that it solves these challenges. Data was collected from existing records of flight schedules and passenger bookings. The data collected was used as input to an optimisation model for passenger recovery. Scrum Agile Development methodology was adopted as the software methodology for developing the solution. A proof of concept web application was developed to make passenger recovery easier and reduce operational cost and passenger delay time. An optimization model was developed based on IBM ILOG CPLEX optimiser to help solve disruptions faster. Testing was conducted by both the developer and a selected sample of airline industry users

Multi-Scale Models for Transportation Systems Under Emergency Conditions

In recent years natural disasters have caused significant disruptions to transportation systems, which had to cascade negative impacts on humanitarian operations, related infrastructure, and associated industries in the affected areas. How to prepare for and respond to transportation system disruptions is a complex decision incorporating a variety of factors, from system use to system preparation. To address these challenges, the project team has developed optimization models for flight rescheduling and road restoration after a natural disaster and integrated the models as a decisionmaking tool. The data of North Carolina emergency response activities, air flights, and road closures during Hurricane Matthew were used to test the models and tool. The testing results show that the integrated tool can quickly find optimal sets and sequences for road restoration and flight schedules recovery at an affected airport and 50 counties. The tool can also visualize the damaged connections between counties, airports and resource centers, and the road restoration schedule and flight schedules recovery plan. The optimization models and decision-making tool developed in this project can support deploying effective restoration and recovery of transportation systems during an emergency event, which can improve the mobility of people and disaster relief under emergency

A novel passenger recovery approach for the integrated airline recovery problem

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record Schedule disruptions require airlines to intervene through the process of recovery; this involves modifications to the planned schedule, aircraft routings, crew pairings and passenger itineraries. Passenger recovery is generally considered as the final stage in this process, and hence passengers experience unnecessarily large impacts resulting from flight delays and cancellations. Most recovery approaches considering passengers involve a separately defined module within the problem formulation. However, this approach may be overly complex for recovery in many aviation and general transportation applications. This paper presents a unique description of the cancellation variables that models passenger recovery by prescribing the alternative travel arrangements for passengers in the event of flight cancellations. The results will demonstrate that this simple, but effective, passenger recovery approach significantly reduces the operational costs of the airline and increases passenger flow through the network. The integrated airline recovery problem with passenger reallocation is solved using column-and-row generation to achieve high quality solutions in short runtimes. An analysis of the column-and-row generation solution approach is performed, identifying a number of enhancement techniques to further improve the solution runtimes.Australian Research Council Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS

Flight disruptions : passenger recovery

BibliografiaEl proyecto consiste en desarrollar un algoritmo que ayude a las aerolíneas a encontrar la mejor solución cuando, después de interrupciones, se tiene que gestionar la planificación inicial de los vuelos, y conseguir recuperar tanto las aeronaves como a los pasajeros para que les afecte lo mínimo posible, y de esta manera, que estas interrupciones tengan un menor coste para las aerolíneas. Esto se realizará a partir de las referencias bibliográficas de Bisaillon, Cordeau, Laporte y Pasin (2010) donde se intenta encontrar una solución óptima que se acerque lo máximo posible a la solución que proponen ellos en su artículo

Gestió de les disrupcions : vaga ATC França 21-03-16

El projecte consistirà en realitzar una overview de les interrupcions que tenen lloc en el departament d'OCC (Centre de Control d'Operacions), a més de la descripció dels problemes que es produeixen a causa d'aquestes i el procés de solució que es dur a terme. Posteriorment, s'analitzaran profundament els problemes d'aircraft recovery i passenger recovery, dels quals es buscarà una solució a través d'un algorisme. La finalitat és augmentar l'eficiència del procés de la presa de decisions en el Departament, per poder fer front al creixement del transport aeri mitjançant l'optimització i automatització dels processos.El proyecto consistirá en realizar una overview de las interrupciones que tienen lugar en el departamento de OCC (Centro de Control de Operaciones), además de la descripción de los problemas que se producen a causa de éstas i el proceso de solución que se lleva a cabo.Posteriormente, se analizaran profundamente los problemas d'aircraft recovery y passenger recovery, de los cuáles se buscará una solución a través de un algoritmo. La finalidad es aumentar la eficiencia del proceso de la toma de decisiones en el Departamento, para poder hacer frente al crecimiento del transporte aéreo mediante la optimización i la automatización de los procesos.This project is based on an overview of the disruptions that take place in the OCC (Operations Control Center) department, as well as the description of the involved problems and the solution process that is carried out. Two of the main disruptions, Aircraft and passenger recovery problems, are analyzed in detail and a solution algorithm is sought. The aim is to increase the efficiency of the decision making process in the Department, in order to cope with the growth of the air transport industry through the optimization and automation of processes

Central authority controlled air traffic flow management: An optimization approach.

Despite various planning efforts, airspace capacity can sometimes be exceeded, typically due to disruptive events. Air traffic flow management (ATFM) is the process of managing flights in this situation. In this paper, we present an ATFM model that accounts for different rerouting options (path rerouting and diversion) and pre-existing en-route flights. The model proposes having a central authority to control all decisions, which is then compared with current practice. We also consider inter-flight and inter-airline fairness measures in the network. We use an exact approach to solve small-to-medium-sized instances, and we propose a modified fix-and-relax heuristic to solve large-sized instances. Allowing a central authority to control all decisions increases network efficiency compared to the case where the ATFM authority and airlines control decisions independently. Our experiments show that including different rerouting options in ATFM can help reduce delays by up to 8% and cancellations by up to 23%. Moreover, ground delay cost has much more impact on network decisions than air delay cost, and network decisions are insensitive to changes in diversion cost. Furthermore, the analysis of the trade-off between total network cost and overtaking cost shows that adding costs for overtaking can significantly improve fairness at only a small increase in total system cost. A balanced total cost per flight among airlines can be achieved at a small increase in the network cost (0.2 to 3.0%) when imposing airline fairness. In conclusion, the comprehensiveness of the model makes it useful for analyzing a wide range of alternatives for efficient ATF