Multi-criteria route optimization for dangerous goods transport using fuzzy risk assessment and agent-based traffic simulation

Abstract : Everyday thousands of trucks transporting hundreds of thousands of tons of dangerous goods by various modalities and both within and across nations. However, the term “dangerous” indicates an intrinsic adversity that characterize these products, which can manifest in an accident leading to release of a hazardous substance (e.g. radioactive, flammable, explosive etc.). In this situation, the consequences can be lethal to human beings, other living organisms and damage the environment and public/private properties.The importance of dangerous goods boils down to the significant economic benefits that generates. In fact, one cannot deny the contribution of the transport of all fossil fuel derived product, which represents more than 60% of dangerous goods transported in Europe. Eni, the Italian leading petrochemical company, every day operates a fleet of about 1,500 trucks, which performs numerous trips from loading terminals to filling stations. Distribution of petroleum products is a risky activity, and an accident during the transportation may lead to serious consequences.Aware of what is at stake, the division Eni R&M - Logistics Secondary, historically active in Genoa headquarters, is collaborating since 2002 with the DIBRIS department at University of Genoa, and the CRC at Mines ParisTech, with the purpose of studying possible improvements regarding safety in transport of dangerous goods, particularly petroleum products. Over years, this collaboration has led to the development of different technologies and mainly to an information and decision support system. The major component of this system is a platform for monitoring Eni fleet, at the national level, to deliver the products to the distribution points, called the Transport Integrated Platform (TIP). These vehicles are equipped with a device capable of transmitting data stream in real-time using a GPRS modem. The data transmitted can be of different nature and contain information about the state of the vehicle and occurred events during the trip. These data are intended to be received by centralized servers then get processed and stored, in order to support various applications within the TIP.With this in mind, the studies undertaken throughout the thesis are directed towards the development of a proposal to further minimize the risk related to the transportation of dangerous goods. In other words, a trade-off based model for route selection taking into consideration economic and safety factors. The objective is prompted by the need to support existent regulations and safety standards, which does not assure a full warranty against accidents involving dangerous goods.The goal is carried out by considering the existent system as basis for developing an Intelligent Transportation System (ITS) aggregating multiple software platforms. These platforms should allow planners and decision makers to monitor in real-time their fleet, to assess risk and evaluate all possible routes, to simulate and create different scenarios, and to assist at finding solutions to particular problems.Throughout this dissertation, I highlight the motivation for such research work, the related problem statements, and the challenges in dangerous goods transport. I introduce the TIP as the core for the proposed ITS architecture. For simulation purposes, virtual vehicles are injected into the system. The management of the data collection was the subject of technical improvement for more reliability, efficiency and scalability in real-time monitoring of dangerous goods shipment. Finally, I present a systematic explanation of the methodology for route optimization considering both economic and risk criteria. The risk is assessed based on various factors mainly the frequency of accident leading to hazardous substance release and its consequences. Uncertainty quantification in risk assessment is modelled using fuzzy sets theory.
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Mohamed Haitam Laarabi. Multi-criteria route optimization for dangerous goods transport using fuzzy risk assessment and agent-based traffic simulation. Business administration. Ecole Nationale Supérieure des Mines de Paris, 2014. English. ⟨NNT : 2014ENMP0074⟩. ⟨tel-01145363⟩



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