Search

An increasing freight demand is putting pressure on the freight transport network, forced to pay high costs to ensure compliance with the conditions and delivery times, as well as to grow towards environmental sustainability. The purpose of this paper is to analyse the main drivers for choosing the type of transport in the planning of distribution logistics through the application of the Multinomial Logit Model (MLN) under the objective of CO2 emission minimisation in order to identify the most sustainable transport solution as a function of distance along the same lines as Hoover’s diagrams. The approach has been applied to a real case study (the logistics department of an Italian manufacturing company) in order to define the mode of transport that minimises the quantity of carbon dioxide emitted and therefore to analyse the effect that this modal shift strategy has on the other selection drivers. The results were encouraging in guiding the application of a modal shift strategy and the change to more sustainable transport modes: 62.5% of the company’s transport shipments should be transferred from road to a different mode, with an overall reduction of 41% of CO2 emissions, without any impact on costs and delivery time. [ABSTRACT FROM AUTHOR]

In the recent years, the scope of environmental studies has expanded dramatically all over the world. This paper aims to build a system based on fuzzy models that can be implemented in the assessment of ecological systems, to determine appropriate methods of action for reducing adverse effects on environmental and implicit the population. It is noted that this subject of research represent a high interest current in the world. In situations difficult to approach methods with modeling conventional, are proposed as a reliable alternative pathways to fuzzy logic-based modeling. Information systems may determine, based on data supplied by the beneficiary (government agencies, local authorities, economic agents), appropriate methods of action for reducing adverse effects on industry, agriculture, forestry, water management and human settlements. Fuzzy algorithms in this field is new, and presume definition, clear delimitation and the analysis of the system which performing the tasks specified. [ABSTRACT FROM AUTHOR]