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The supply chains of perishable food (PFSC) fresh, present imbalances between supply and demand, in times of supply deficit is necessary to guarantee the food security through the availability, the access and other pillars. In the PFSC losses are highest, whereby the delivery times must be low to guarantee the availability. For the access, must be include the largest number of retailed storekeepers, thus monopolies from large hypermarkets are avoided. In this context, the modeling In PFSC presents big challenges such as the inclusion of delivery times, losses and fresh food biophysical specific conditions which depend of the transport time and storage, the configuration and the number of echelons on the PFSC. In this article, a multiobjective, multiproduct and multi-echelon for perishable food logistics networks design mixed linear programming model is presented. The model allows determining the best configuration so that the different actors of the PFSC, so that could move closer to more efficient borders. The model considers the losses in perishable food derived from the impacts caused by changes in temperature (T°) and relative humidity (RH), on a mountainous environment of developing countries. It is solved in AMPL through e-constrains method. The model is applied in a case study around the perishable fruit supply chains (PFrSC). The information to the model parameterization was obtained through surveys done to the actors of the different echelons of PFrSC during a 4-year period that were complemented with secondary information from public and private enterprises. [ABSTRACT FROM AUTHOR]

Purpose: A common problem in mega cities is congestion, due to the size of the automotive park, this makes that the perishable foods decreasing their organoleptic characteristics or increases their losses, which requires considering the effect of time on routing problems. The state of the art demonstrates the need to formulate new routing models that include the specific characteristics of perishable foods in order to reduce their losses. Design/methodology/approach: A mathematical model was formulated based on two classical models: the three-index vehicle flow model proposed by (Golden, Assad, Levy & Gheysens, 1984) and the time window model proposed by (Cordeau, Desaulniers, Desrosiers, Solomon & Soumis, 1999). We proposed a novel VRP Model that permits reductions loss due to the perishable. Findings: The optimum cost is found with AMP® for twenty nodes, six vehicles and six fruits. For more nodes, a two-phase strategy is proposed, first a clustering based on a modified p-median model and then a VRP for each cluster. Research limitations/implications: The results showed the need to investigate multiobjective models, since the performance measures can be efficiency, quality and response capacity; the model can be applied in other supply chains of perishable foods. Social implications: According to FAO in Logistics practices in the last mile generate between 10-30% of the perishable food loss in developing countries' mega-cities. Originality/value: A last-mile logistics strategy is proposed to manage delivery routes for fresh fruits in mega-cities, considering the effect of congestion through travel time in the perishability function. The new model it uses the flow variable to control the amount of each fruit arriving to each node and the time variable to define fruit waste or loss depending on the time and type of fruit. [ABSTRACT FROM AUTHOR]

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