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Thesis

French

ID: <

http://hdl.handle.net/20.500.11794/38087

>

Where these data come from
Advanced decision making in sustainable city logistics projects : criteria and, risk identification and assessment

Abstract

The cities are the places of the largest concentration of social activities and economic. Logistics is one of the most important for the sustainability and the economy of the city. Inselecting the city logistics concept, it is necessary to consider the characteristics of the city and the goals of all the stakeholders (shippers, receivers, carriers, logistics service providers, residents, city government). Sustainable city logistics (SCL) plans could significantly affect the quality of life in the urban environment. Evaluating sustainable city logistics initiatives (SCLI) such as urban distribution centres, congestion pricing, delivery timing and access restrictions is a complex problem since several subjective and objective criteria and constraints should be considered. Municipal administrations are investing in sustainable city logistics initiatives (SCLI) such as urban distribution centres, congestion pricing, delivery timing and access restrictions in order to improve the condition of goods transport in cities and reduce their negative impacts on citizens and their environment. However, there is always some dynamic risks associated that should be selected. Risk analysis of sustainable city logistics initiatives is a complex task due to consisting of many risk factors with dependencies among them. Although there are no lots of studies on sustainable city logistics risks, no attention has been paid to the risk analysis of sustainable city logistics by considering the dependencies among risk factors and their criteria. Considering the dependencies among risk factors could lead to more precise risks analysis and increase the success rate of selecting sustainable city logistics initiatives. Methods: To address this, we are proposing an advanced decision support tool called "Fuzzy Cognitive Maps" (FCM) which can deal with risks of such complicated systems. FCM represents the behaviour of complex systems accurately and is able to consider uncertainties, imprecise information, the interactions between risk factors, information scarcity, and several decision maker's opinions. In addition, it could be applied to different decision makings problems related to sustainable city logistics initiatives (SCLI). Therefore, the proposed tool would help practitioners to manage sustainable city logistics risks in a more effective and proactive way and offer better risk mitigation solutions. In previous studies, multi-criteriadecision-making methods are mainly used for the evaluation, comparison and selection of individual sustainable city logistics initiatives in relation to the achieved or planned effects resulting from their introduction in various urban environments. In order to assess the suitability of the conceptual solutions to the requirements of different stakeholders, and in accordance with the specific attributes of the urban environment, there is the definition of conceptual solutions that combine different sustainable city logistics initiatives by using an artificial; intelligence tools including FCM.

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