This thesis on the topic "Insurance of pilots and cabin crew" deals with one of the professional groups of insured which in this case are pilots and cabin crew - the frontline staff on board of a commercial aircraft. It characterizes risks associated with these types of profession and possible ways of their elimination by insurance with a particular focus on health and travel insurance. The last chapter of this work also analyzes an offer of travel insurance suitable for pilots and cabin crew and it refers to exceptions from insurance claims related to the performance of these jobs.

Background Being able to learn from mistakes is a vital aspect of nurse’s professionalism and increasing patient safety. With Crew Resource Management methodologies, aviation and other High Risk Organisations have succeeded in enabling learning cultures that should be applicable also to healthcare. Purpose The purpose was to describe how Crew Resource Management and the inherent learning culture could improve nurse’s professionalism and patient safety within the healthcare system.  Method A literature overview based on database searches in CINAHL, PubMed and a manual search, resulting in 25 scientific articles analysed using an integrated analysis method and quality review.  Results Crew Resource Management implementations have a positive effect on the nurse’s professional role and patient safety but have still not reached the full potential. Incident reporting is a key factor in providing feedback but still encounters barriers as a basis for pre-emptive learning. Identified barriers are not using Crew Resource Management components as a whole, a lack of feedback and an insufficient learning culture. Feedback is connected to nurse’s perception and situational awareness strengthening morale and professionalism. Conclusion Nurses professionalism and patient safety is dependent on being able to learn from mistakes which is a key aspect of Crew Resource Management. Learning is enabled by the reporting of mistakes in incident reporting systems without the fear of being punished. Improvements to both systems and the reporting culture are seen as needed, as-well as changes to the education system promoting reporting as part of an overall safety and learning culture.

Thesis: M.S., Massachusetts Institute of Technology, Department of Civil Engineering, 1978 / Bibliography: leaves 73-74. / M.S. / M.S. Massachusetts Institute of Technology, Department of Civil Engineering

This study seeks to determine through survey research what characteristics film production crews possess that makes them so successful as an organization. The factors of age, gender, years of professional experience and education level were tested for their significance on how the respondents view their culture. Hofstede's six dimensions of organizational culture survey questions were rewritten to be applicable to the freelance film crew sample. The presentation of findings focuses on the resultant organizational profile of a film production crew, the workplace values of this group and the influence that the education level of the participants had on responses. The data presented here are valuable for organizational culture scholars, management scholars and those interested in applying the successful techniques of the film production crew to other business organizations.

Crew race strategy is typically formulated by coaches based on rowing tradition and years of experience. However, coaching strategies are not generally supported by empirical evidence and decision-support models. Previous models of crew race strategy have been constrained by the sparse information published on crew race performance (quarterly 500-meter splits). Empirical research has merely summarized which quarterly splits averaged the fastest and slowest relative to the other splits and relative to the average speed of the other competitors. Video records of crew race world championships provide a rich source of data for those capable and patient enough to mine this level of detail. This dissertation is based on a precise frame-by-frame video analysis of five world championship rowing finals. With six competing crews per race, a database of 75 race-pair duels was compiled that summarizes race positioning, competitive drives, and relative stroke rates at 10-meter intervals recorded with photo-finish precision (30 frames per second). The drive-based research pioneered in this dissertation makes several contributions to understanding the dynamics of crew race strategy and performance: 1) An 8-factor conceptual model of crew race performance. 2) A generic drive model that decomposes how pairs of crews duel in a race. 3) Graphical summaries of the rates and locations of successful and unsuccessful drives. 4) Contour lines of the margins that winning crews hold over the course of the race. 5) Trend lines for what constitutes a probabilistically decisive lead as a function of position along the course, seconds behind the leader, and whether the trailing crew is driving. This research defines a new drive-based vocabulary for evaluating crew race performance for use by coaches, competitors and race analysts. The research graphically illustrates situational parameters helpful in formulating race strategy and guiding real-time decision-making by competitors. This research also lays the foundation for future industrial engineering decision-support models and associated parameters as applied to race strategy and tactics.

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Cette thèse développe des algorithmes pour les problèmes de plus court chemin sous cont-rain-tes de ressources, et les applique à l'optimisation des rotations des avions et des équipages d'une compagnie aérienne dans le cadre d'approches par génération de colonnes.Les problèmes de plus court chemin sous contraintes de ressources sont généralement résolus grâce à une énumération intelligente de tous les chemins non dominés. Les approches récentes utilisent des bornes sur les ressources des chemins pour éliminer des solutions partielles. L'efficacité de la méthode est conditionnée par la qualité des bornes utilisées. Notre principale contribution au domaine est l'introduction d'une procédure générique pour calculer des bornes qui s'applique à la plupart des problèmes de chemins sous contraintes, et en particulier les problèmes stochastiques. A cette fin, nous introduisons une généralisation du problème de plus court chemin sous contraintes dans laquelle les ressources des chemins appartiennent à un monoïde ordonné comme un treillis. La ressource d'un chemin est la somme des ressources de ses arcs, le terme somme désignant l'opérateur du monoïde. Le problème consiste à trouver parmi les chemins qui satisfont une contrainte donnée celui dont la ressource minimise une fonction de coût croissante de la ressource des chemins. Nous généralisons les algorithmes d'énumération à ce nouveau problème. La théorie des treillis nous permet de construire une procédure polynomiale pour trouver des bornes de qualité. L'efficacité pratique de la méthode est évaluée au travers d'une étude numérique détaillée sur des problèmes de chemins déterministes et stochastiques. Les procédures de calcul des bornes peuvent être interprétées comme des généralisations aux monoïdes ordonnés comme des treillis d'algorithmes de la littérature définis pour résoudre un problème de chemin pour lequel les ressources des chemins prennent leur valeur dans un semi-anneau.Nos algorithmes de chemins ont été appliqués avec succès au problème de crew pairing. Étant donné un ensemble de vols opérés par une compagnie aérienne, les problèmes d'aircraft routing et de crew pairing construisent respectivement les séquences de vols opérées par les avions et par les équipages de manière à couvrir tous les vols à moindre coût. Comme certaines séquences de vols ne peuvent être réalisées par un équipage que s'il reste dans le même avion, les deux problèmes sont liés. La pratique actuelle dans l'industrie aéronautique est de résoudre tout d'abord le problème d'aircraft routing, puis le problème de crew pairing, ce qui aboutit à une solution non-optimale. Des méthodes de résolution pour le problème intégré ont été développées ces dix dernières années. Nous proposons une méthode de résolution pour le problème intégré reposant sur deux nouveaux ingrédients : un programme linéaire en nombre entier compact pour le problème d'aircraft routing, ainsi que de nouveaux pour le problème esclave de l'approche usuelle par génération de colonnes du problème de crew pairing. Ces algorithmes pour le problème esclave sont une application de nos algorithmes pour le problème de plus court chemin sous contraintes. Nous généralisons ensuite cette approche de manière à prendre en compte des contraintes de probabilités sur la propagation du retard. Ces algorithmes permettent de résoudre quasiment à l'optimum les instances industrielles d'Air France / This thesis develops algorithms for resource constrained shortest path problems, and uses them to solve the pricing subproblems of column generation approaches to some airline operations problems.Resource constrained shortest path problems are usually solved using a smart enumeration of the non-dominated paths. Recent improvements of these enumeration algorithms rely on the use of bounds on path resources to discard partial solutions. The quality of the bounds determines the performance of the algorithm. Our main contribution to the topic is to introduce a standard procedure to generate bounds on paths resources in a general setting which covers most resource constrained shortest path problems, among which stochastic versions. In that purpose, we introduce a generalization of the resource constrained shortest path problem where the resources are taken in a lattice ordered monoid. The resource of a path is the monoid sum of the resources of its arcs. The problem consists in finding a path whose resource minimizes a non-decreasing cost function of the path resource among the paths that satisfy a given constraint. Enumeration algorithms are generalized to this framework. We use lattice theory to provide polynomial procedures to find good quality bounds. The efficiency of the approach is proved through an extensive numerical study on deterministic and stochastic path problems. Interestingly, the bounding procedures can be seen as generalizations to lattice ordered monoids of some algebraic path problem algorithms which initially work with resources in a semiring.Given a set of flight legs operated by an airline, the aircraft routing and the crew pairing problem build respectively the sequences of flight legs operated by airplanes and crews at minimum cost. As some sequences of flight legs can be operated by crews only if they stay in the same aircraft, the two problems are linked. The current practice in the industry is to solve first the aircraft routing, and then the crew pairing problem, leading to a non-optimal solution. During the last decade, solution schemes for the integrated problem have been developed. We propose a solution scheme for the integrated problem based on two new ingredients: a compact integer program approach to the aircraft routing problem, and a new algorithm for the pricing subproblem of the usual column generation approach to the crew pairing problem, which is based on our resource constrained shortest path framework. We then generalize the algorithm to take into account delay propagation through probabilistic constraints. The algorithms enable to solve to near optimality Air France industrial instances

Crew pairing and vehicle routing are combinatorial optimization problems that have been studied for many years by researchers worldwide. The aim of this research work is to investigate effective methods for solving large scale crew pairing problems and vehicle routing problems. In the airline industry, to address the complex nature of crew pairing problems, we propose a duty tree method followed by a primal-dual subproblem simplex method. The duty tree approach captures the constraints that apply to crew pairings and generate candidate pairings taking advantage of various proposed strategies. A huge number of legal pairings are stored in the duty tree and can be enumerated. A set partitioning formulation is then constructed, and the problem is solved using a primal-dual subproblem simplex method tailored to the duty tree approach. Computational experiments are conducted to show the effectiveness of the methods. We also present our efforts addressing the capacitated vehicle routing problem (CVRP) that is the basic version of many other variants of the problem. We do not attempt to solve the CVRP instances that have been solved to optimality. Instead, we focus on investigating good solutions for large CVRP instances, with particular emphasis on those benchmark problems from the public online library that have not yet been solved to optimality by other researchers and determine whether we can find new best-known solutions. In this research, we propose a route network that can store a huge number of routes with all routes being legal, a set partitioning formulation that can handle many columns, and the primal-dual subproblem simplex method to find a solution. The computational results show that our proposed methods can achieve better solutions than the existing best-known solutions for some difficult instances. Upon convergence of the primal-dual subproblem simplex method on the giant-tour based networks, we use the near optimal primal and dual solution as well as solve the elementary shortest path problem with resource constraints to achieve the linear programming relaxation global optimal solution.

Esta pesquisa trata o Problema de Programação de Tripulantes (PPT), presente no planejamento operacional das empresas aéreas. O principal objetivo do PPT é atribuir um conjunto de tarefas aos tripulantes, considerando as regulamentações trabalhistas, as regras de segurança e as políticas das empresas, de tal maneira que o custo da tripulação seja mínimo. O PPT é normalmente dividido em dois subproblemas, resolvidos sequencialmente: Problema de Determinação das Viagens (PDV) e Problema de Atribuição de Escalas (PAE). No PDV, determina-se um conjunto de viagens que cubra todos os voos planejados. Em seguida, no PAE, as escalas, compostas pelas viagens escolhidas e outras atividades como folgas, sobreavisos, reservas, treinamentos e férias, são atribuídas aos tripulantes. Esta decomposição justifica-se pela natureza combinatória do PPT, porém não incorpora as disponibilidades e as preferências dos tripulantes em ambos os subproblemas (PDV e PAE), gerando assim custos extras relacionados aos conflitos que surgem durante a atribuição das escalas aos tripulantes no PAE. Além disso, as estimativas de custos adotadas no PDV não possuem caráter global, já que o custo real da programação só pode ser obtido após a atribuição das escalas. O estado da arte envolve a solução integrada do PPT, em que se elimina a necessidade de resolver inicialmente o PDV, provendo assim uma melhor estimativa de custo e uma programação final com melhor qualidade, por considerar os custos da tripulação, as disponibilidades e preferências dos tripulantes de forma global. O problema, no entanto, é NP-Difícil. Assim sendo, a metodologia proposta nesta pesquisa objetiva a solução do PPT de forma integrada, através de um Algoritmo Genético Híbrido (AGH) associado a um procedimento de busca em profundidade, levando em conta as particularidades da legislação brasileira. A metodologia foi testada, com sucesso, para a solução de instâncias baseadas na malha real de uma empresa aérea brasileira. / This master of science research treats the Crew Scheduling Problem (CSP), as part of the airlines operational planning. The main aim of the CSP is to assign a set of tasks to crew members, considering the labor regulations, safety rules and policies of companies, such that the crew cost is minimal. The CSP is divided into two subproblems, solved sequentially: Crew Pairing Problem (CPP) and Crew Rostering Problem (CRP). First, CPP provides a set of pairings that covers all the planned flights. Then, in the CRP, the rosters, encompassing the pairings and other activities such as rest periods, alert duties, reserve duties, training times and vacations, are assigned to the crew members. This decomposition is justified by the combinatorial nature of the CSP, but it not incorporates the crew members availabilities and preferences in both subproblems (CPP and CRP), generating extra costs related to conflicts that arise during the assignment of rosters to the crew members in the CRP. Besides, the costs estimations adopted in the CPP does not have a global character, since the real cost of the global schedule can be only obtained after the assignment of the rosters. The state of the art involves the integrated solution of CSP, where the CPP does not need to be solved, thus providing a better estimated cost and a better schedule quality, considering crew costs and also crew members availabilities and preferences globally. The problem, however, is NP-Hard. Therefore, the methodology proposed in this master of science research aims to obtain an integrated solution of the CSP, through an hybrid algorithm genetic associated with a depth-first search procedure, taking into account the Brazilian legislation. The methodology was tested, with success, to solve instances related a real network of a Brazilian airline.