Abstract:Purpose: The contribution of this research is to propose a new problem of linear-mixed programming model (LMPM) for the allocation-packing of multiple pantries personalized for Food Banks (FB) considering the opinion of the Decision Maker (DM) in the selection of the best solution.Design/methodology/approach: A food allocation-packing system is modeled as a mixed integer problem (MIP) and a fuzzy mixed integer linear problem (FMILP). 250 families and 100 products were considered. The solutions were found using Lingo 13® (for both deterministic and fuzzy model). To select a good solution in the fuzzy model, this research adapted an interactive method proposed in the literature. The relevance of this modification is that the opinion of a decision maker (DM) is included and considered. Findings:The results for the deterministic and fuzzy model are compared in terms of their accomplishment of the restrictions (mainly nutritional and logistic) and the time needed to achieve a solution.Research limitations/implications: This paper was done considering quantity, weight and volume restrictions so that the pantry will contain a variety of products; it is not considered how the products will be stored into the pantry. Keywords: humanitarian logistics, diet and food packing problems, fuzzy mixed-integer linear programming, perishable and nonperishable food, food bank

Identifying the most efficient supply system for a company working under Lean Manufacturing practices was possible with the support of this work. Promodel software was used to develop simulation model depicting a constant velocity joints (CVJ) production system, where two different supply methods were assessed. According to results herein obtained, better performance is achieved under random supply method in comparison with a clustering supply method. The company's goal is to keep 1% losses due to lack of material. In the actual process, this essential parameter was reduced from 2.73% to 1.177%, if random supply method is properly implemented.

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