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This book focuses on real time management of distribution systems, integrating the latest results in system design, algorithm development and system implementation to capture the state-of-the art research and application trends. The book important topics such as goods dispatching, couriers, rescue and repair services, taxi cab services, and more. The book includes real-life case studies that describe the solution to actual distribution problems by combining systemic and algorithmic approaches.
Two new dynamic planning approaches, incorporating all important real-life restrictions, such as regulations on driving and working hours, are developed and evaluated. Extensive numerical tests are carried out with a five-week real-life data set from an international freight forwarding company.
Fleet management made simple, written around management of public fleet assets. Easy to read, simple easy to use formulas and concepts developed by author after a lifetime spent in equipment maintenance and fleet management. A must read for those seeking success in public sector fleet management.
Esta dissertação tem como objetivo contribuir para o gerenciamento de frotas de grande porte, buscando uma maior rapidez e eficiência na distribuição de veículos ao longo do tempo/espaço, visando maximizar o lucro total da empresa. Problemas de gerenciamento de frotas dinâmicas são normalmente formulados como uma rede dinâmica, mas há uma grande dificuldade ao se trabalhar com problemas desse tipo, especialmente quando se busca uma solução sobre umhorizonte de planejamento longo. Visando contornar essa dificuldade, Powell & Carvalho (1998) desenvolveram uma nova abordagem para problemas desse tipo: a Logistics Queuing Network (LQN). A utilização do algoritmo LQN na prática (através de um software) permitiria uma tomada de decisão mais rápida e eficiente, sendo bastante útil, em especial para empresas de transportes. Assim, implementou-se o algoritmo LQN, através do desenvolvimento de um software para o gerenciamento de frotas de grande porte, por meio do qual podeseconstatar o potencial de aplicação desse algoritmo.
TEODOR GABRIEL CRAINIC, DIRECTOR The Centre for Research on Transportation (C.R.T.) was founded in 1971 by the Universite de Montreal. From 1988 on, it is jointly managed by the Universite de Montreal and its affiliated schools, the Ecole des Hautes Etudes Commerciales and Ecole Poly technique. Professors, students and researchers from many institutions in the Montreal area join forces at the C.R.T. to analyze transportation, logistics and telecommunication systems from a multidisciplinary perspective. The C.R.T. pursues three major, complementary objectives: training of high-level specialists; the advancement of knowledge and technology; the transfer of technology towards industry and the public sector. Its main field of expertise is the develop ment of quantitative and computer-based models and methods for the analysis of urban, regional and intercity transportation networks, as well as telecommunication systems. This applies to the study of passenger and commodity flows, as well as to the socioeconomic aspects of transportation: policy, regulation, economics. The twenty-fifth anniversary of the C.R.T. offered the opportunity to evaluate past accomplishments and to identify future trends and challenges. Five colloquia were thus organized on major research and application themes that also reflected our main research areas. They gathered together internationally renowned researchers who linked recent scientific and technological advances to modeling and methodological challenges waiting to be tackled, particularly concerning new problems and applica tions, and the increasingly widespread use of new technologies.
Autonomous vehicles (AVs) have been heralded as the key to unlock a shared mobility future where transportation is more efficient, convenient, and cheaper. However, the AV utopia can only come to fruition if the majority of users trust that autonomous mobility-on-demand (AMoD) systems are on a par with owning a vehicle in terms of service quality. Once the perception of quality is highly subjective, we propose a more personalized approach to on-demand mobility, in which users are segmented into service quality classes. These classes comprise minimum requirements regarding responsiveness and privacy, allowing us to model a series of user profiles formalized using strict service quality contracts. By honoring these contracts, providers can build users' trust and gain their loyalty, which on a grander scheme can contribute to a faster transition to a shared mobility future. This thesis presents a series of strategies to guaranteeing service quality throughout operational scenarios arising in the timeline of AV technology deployment. First, a precondition to providing service quality in autonomous transportation is safety. During a transition phase to full automation, AV operation will likely be restricted to areas where safe operations are guaranteed, leading to the formation of hybrid street networks comprised of autonomous and non-autonomous vehicle zones. In this setting, meeting user service quality expectations is primarily a matter of coverage, once mobility services will have to access both AV-ready and not AV-ready areas. Accordingly, this thesis proposes solutions to overcome the challenges entailed by such a transition scenario, where infrastructures, regulatory measures, and AV technology are gradually evolving. Then, assuming that widespread automated driving is the new status quo, we set out to model rich autonomous transportation scenarios comprised of heterogeneous users and vehicles. Central to our analysis is finding an adequate trade
This book deals with transportation processes denoted as the Real-time Distribution of Perishable Goods (RDOPG). The book presents three contributions that are made to the field of transportation. First, a model considering the minimization of customer inconvenience is formulated. Second, a pro-active real-time control approach is proposed. Stochastic knowledge is generated from past request information by a new forecasting approach and is used in the pro-active approach to guide vehicles to request-likely areas before real requests arrive there. Various computational results are presented to show that in many cases the pro-active approach is able to achieve significantly improved results. Moreover, a measure for determining the structural quality of request data sets is also proposed. The third contribution of this book is a method that is presented for considering driver inconvenience aspects which arise from vehicle en-route diversion activities. Specifically, this method makes it possible to restrict the number of performed vehicle en-route diversion activities.​