Business Benefits Associated With Improving Fatigue Regulations for Cargo Pilots

The central idea of this research is to assess business-related factors in the Pilots ́ Fatigue Regulations and evaluate if a more flexible regulation would improve productivity of airline cargo pilots in Brazil. The results of the study have indicated that Brazilian Civil Aviation Authority (ANAC) can create a regulatory environment that may lead up to 34,28% of improved productivity of pilots ́ availability in cargo operations, which may contribute for gains up to USD $3.6 million for an airline with cargo 70 pilots flying 16.500 hours per year. Aviation fatigue regulations are an extremely important subject in the aviation industry as they are a part of an evolution of operational processes within the Safety Management System (SMS). However, some restrictions in regulation may produce some business-related inefficiencies in terms of additional costs or revenue loss to airline companies. The research conducted revised the bibliography available with regards this subject of pilots ́ fatigue regulation in the USA and Brazil. The Group also compared important business-related indicators related to cargo pilots ́ operations in Brazil and calculated potential gains of a hypothetical scenario with an adjusted pilot ́s schedule in line with FAA CFR 177. At last, the research included evaluation of The National Transportation Safety Board (NTSB) records of events of cargo operations in the USA to compare if safety is impacted by fatigue in an environment of an optimized schedule of cargo pilot. A crucial finding of this research is that the proposed changes shall not impact current safety levels caused by fatigue of pilots

Improving robustness of rolling stock circulations in rapid transit networks

The rolling stock circulation depends on two different problems: the rolling stock assignment and the train routing problems, which up to now have been solved sequentially. We propose a new approach to obtain better and more robust circulations of the rolling stock train units, solving the rolling stock assignment while accounting for the train routing problem. Here robustness means that difficult shunting operations are selectively penalized and propagated delays together with the need for human resources are minimized. This new integrated approach provides a huge model. Then, we solve the integrated model using Benders decomposition, where the main decision is the rolling stock assignment and the train routing is in the second level. For computational reasons we propose a heuristic based on Benders decomposition. Computational experiments show how the current solution operated by RENFE (the main Spanish train operator) can be improved: more robust and efficient solutions are obtaine

Smooth and controlled recovery planning of disruptions in rapid transit networks

This paper studies the disruption management problem of rapid transit rail networks. We consider an integrated model for the recovery of the timetable and the rolling stock schedules. We propose a new approach to deal with large-scale disruptions: we limit the number of simultaneous schedule changes as much as possible, and we control the length of the recovery period, in addition to the traditional objective criteria such as service quality and operational costs. Our new criteria express two goals: the recovery schedules can easily be implemented in practice, and the operations quickly return to the originally planned schedules after the recovery period. We report our computational tests on realistic problem instances of the Spanish rail operator RENFE and demonstrate the potential of this approach by solving different variants of the proposed model

A lexicographic optimization approach for berth schedule recovery problem in container terminals

In container terminals, the planned berth schedules often have to be revised because of disruptions caused by severe weather, equipment failures, technical problems and other unforeseen events. In this paper, the problem of berth schedule recovery is addressed to reduce the influences caused by disruptions. A multi-objective, multi-stage model is developed considering the characteristics of different customers and the trade-off of all parties involved. An approach based on the lexicographic optimization is designed to solve the model. Numerical experiments are provided to illustrate the validity of the proposed Model A and algorithms. Results indicate that the designed Model A and algorithm can tackle the berth plan recovery problem efficiently because the beneficial trade-off among all parties involved are considered. In addition, it is more flexible and feasible with the aspect of practical applications considering that the objective order can be adjusted by decision makers

DISRUPTION RECOVERY IN COMMERCIAL AVIATION

This thesis presents three major contributions for commercial aviation planning and disruption recovery in commercial aviation. The first contribution presented in this thesis consists of a flight planning model to calculate Block Time and Fuel (BTF) consumed for an aircraft model during the flight. The BTF model computes the ground distance between the origin and destination airports, derives the flight’s cruise altitude, and by integrating two institutional data sets calculates the duration and the fuel consumed for the whole of taxi-out, take-off, climb, cruise, descent, approach, landing, and taxi-in phases. The model renders very good results for block time and consumed fuel however, it does not consider aircraft weight loss neither the influence of the wind. The second contribution of this thesis consists of a recovery procedure for disrupted aircraft rotations, the Constructive Heuristic for the Aircraft Recovery Problem (CHARP). The CHARP recovers the infeasible rotation combining a meta-heuristic that performs a pincer movement over the search space and Constraint Programming (CP). Additionally, the CHARP uses Constraint Propagation to reduce the size of the search therefore reducing computing. The initial experiments demonstrated that if Constraint Propagation was not used computing time would double. The recovery strategy included flight creation delays and cancellations however it did not include aircraft swap. The third contribution of this thesis combines the BTF model and the CHARP. Since the BTF model returns lower block time flights than those used by the CHARP this thesis investigates six disruption scenarios with shorter block time

Fitness-to-fly and the safety role of air cabin crew: personal, social and managerial challenges

Andrea Sander-Grout investigated the impact of cabin crew fitness-to-fly on flight safety and public health. She found that there is significant uncertainty surrounding crewmember exposure to occupational hazards, with potential impacts on flight safety, individual and public health. Aviation and public health stakeholders are using her results in policy development

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order. The authors dedicate this paper to the 2023 Turkey/Syria earthquake victims. We sincerely hope that advances in OR will play a role towards minimising the pain and suffering caused by this and future catastrophes

AIRO 2016. 46th Annual Conference of the Italian Operational Research Society. Emerging Advances in Logistics Systems Trieste, September 6-9, 2016 - Abstracts Book

The AIRO 2016 book of abstract collects the contributions from the conference participants. The AIRO 2016 Conference is a special occasion for the Italian Operations Research community, as AIRO annual conferences turn 46th edition in 2016. To reflect this special occasion, the Programme and Organizing Committee, chaired by Walter Ukovich, prepared a high quality Scientific Programme including the first initiative of AIRO Young, the new AIRO poster section that aims to promote the work of students, PhD students, and Postdocs with an interest in Operations Research. The Scientific Programme of the Conference offers a broad spectrum of contributions covering the variety of OR topics and research areas with an emphasis on “Emerging Advances in Logistics Systems”. The event aims at stimulating integration of existing methods and systems, fostering communication amongst different research groups, and laying the foundations for OR integrated research projects in the next decade. Distinct thematic sections follow the AIRO 2016 days starting by initial presentation of the objectives and features of the Conference. In addition three invited internationally known speakers will present Plenary Lectures, by Gianni Di Pillo, Frédéric Semet e Stefan Nickel, gathering AIRO 2016 participants together to offer key presentations on the latest advances and developments in OR’s research

Enhanced evolutionary algorithm with cuckoo search for nurse scheduling and rescheduling problem

Nurse shortage, uncertain absenteeism and stress are the constituents of an unhealthy working environment in a hospital. These matters have impact on nurses' social lives and medication errors that threaten patients' safety, which lead to nurse turnover and low quality service. To address some of the issues, utilizing the existing nurses through an effective work schedule is the best alternative. However, there exists a problem of creating undesirable and non-stable nurse schedules for nurses' shift work. Thus, this research attempts to overcome these challenges by integrating components of a nurse scheduling and rescheduling problem which have normally been addressed separately in previous studies. However, when impromptu schedule changes are required and certain numbers of constraints need to be satisfied, there is a lack of flexibility element in most of scheduling and rescheduling approaches. By embedding the element, this gives a potential platform for enhancing the Evolutionary Algorithm (EA) which has been identified as the solution approach. Therefore, to minimize the constraint violations and make little but attentive changes to a postulated schedule during a disruption, an integrated model of EA with Cuckoo Search (CS) is proposed. A concept of restriction enzyme is adapted in the CS. A total of 11 EA model variants were constructed with three new parent selections, two new crossovers, and a crossover-based retrieval operator, that specifically are theoretical contributions. The proposed EA with Discovery Rate Tournament and Cuckoo Search Restriction Enzyme Point Crossover (DᵣT_CSREP) model emerges as the most effective in producing 100% feasible schedules with the minimum penalty value. Moreover, all tested disruptions were solved successfully through preretrieval and Cuckoo Search Restriction Enzyme Point Retrieval (CSREPᵣ) operators. Consequently, the EA model is able to fulfill nurses' preferences, offer fair on-call delegation, better quality of shift changes for retrieval, and comprehension on the two-way dependency between scheduling and rescheduling by examining the seriousness of disruptions

Robust planning in scheduled passenger traffic with applied stochastic programming and integrated risk management

Der Planungsprozess im fahrplanbasierten Passagierverkehr ist eine sehr komplexe Aufgabe und viele Entscheidungen im Planungsprozess müssen unter Unsicherheit getroffen werden. In der langfristigen Planung müssen Fluggesellschaften und Unternehmen des ÖPNVs beispielsweise mit einer Nachfrage-und Treibstoffpreisunsicherheit umgehen. In der kurzfristigen Planung verursachen unvorhersehbare Störungen aufgrund von Wetterbedingungen oder Verkehrsaufkommen Abweichungen vom Plan. Daher ist der Gewinn der Unternehmen in hohem Maße abhängig von der Entwicklung unsicher Parameter. Zum Begrenzen des Risikos in schlechten Szenarien müssen robustere Pläne erstellt werden. Die Robustheit der Pläne kann durch die Integration von Risikomanagement in den Planungsprozess verbessert werden. Die Risiken können mit operativen Methoden, wie z. B. dem Wechsel eines Flugzeugtyps oder der Erhöhung der Pufferzeit zwischen zwei Busfahrten sowie mit kontraktuellen Methoden, wie Hedging der Treibstoffpreise verringert werden. Das Ziel ist, robustere Lösungen für den Planungsprozess im fahrplanbasierten Passagierverkehr zu finden. Bestehende Optimierungsmodelle wurden weiterentwickelt oder neue Modelle wurden von Grund auf entwickelt. Eine integrierte Risikomanagementstrategie wurde in diese Modelle integriert und Fallstudien wurden verwendet, um die Vorteile der robusten Planung nachzuweisen.The planning process in scheduled passenger traffic is a very complex task and many decisions in the planning process have to be fixed under uncertainty. In long-term planning airlines and public transport companies have to cope with demand and fuel price uncertainty, for example. In short-term planning unforeseeable disruptions due to weather conditions or traffic density cause deviations from the plan. As a result, the profit of companies operating in scheduled passenger traffic highly depends on the development of uncertain parameters. To manage and limit the risk of bad scenarios, more robust plans have to be created. The robustness of the plans can be increased by integrating risk management into the planning process. The risks can be decreased with operational methods, such as changing the aircraft type of a flight or increasing the buffer time between two bus trips, as well as with contractual methods, such as hedging fuel prices. The objective is to find more robust solutions for the planning process in scheduled passenger traffic. Existing optimization models are re-developed or new models are developed from scratch, an integrated risk management strategy is integrated into these models, and case studies are used to show the advantages for robust planning.Tag der Verteidigung: 26.09.2012Paderborn, Univ., Diss., 201