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Logistics modeling in supply chain networks is concerned with supporting decision making at strategic, tactical and/or operational level, which can impact chain performances. Strategic decisions may, for instance, involve the optimal number and locations of food processing facilities or warehouses. Tactical decisions involve weekly/monthly production plans that are scheduled ahead in order to fulfill a projected demand for a certain market. Operational decisions are related to day-to-day planning, scheduling and order processing. For each of these decision making levels, logistics modeling tries to determine a set of actions that may improve chain performances, reduce costs, waste, and environmental impact. Logistic modeling may also be employed to fine tune chain operations and ensure compliance with quality and safety regulations.
In the context of Veg-i-Trade, logistic modeling will be employed in order to quantitatively assess the impact of a number of network designs and planning concepts on supply chain costs and product quality & safety, with respect to projected changes that stems from global warming scenarios. Information on the supply chain organization and logistic modeling will be an important input for the elaboration of and running the microbial risk assessments. Scenarios are possible ways in which events may unfold in the future. For instance, a scenario may predict an increase of the average summer temperature in a given area by 0.5 degrees Celsius or a significant decrease of rainfall. Scenarios may impact crop production yields and initial bacteria concentration in fresh produce. Furthermore, they may also impact the growth of a given pathogen within items flowing through the chain. In turn, this may affect the quality of the end products and the amount of waste we will face at the opposite of the chain, in retail shops. For this reason, it is important to include scenarios in the logistic modeling process in order to identify optimal decisions at strategic, tactical and operational level that properly hedge the risk associated with scenarios that are likely to be observed within the planning horizon of interest.