Research on the design of the perishable food supply chain network has increased in recent years. However, little attention has been given to those seasonal foods that generate periods of oversupply and, particularly, to their impact on the sustainability of small producers in developing countries. This research proposes and develops a multi-objective mixed linear programming model for perishable fruits in a south American country at oversupply periods. It minimizes losses and transportation costs and maximizes the inclusion of farmers. It considers four echelons of the supply chain: farms, collection centers, distribution centers and the demand, which is represented by the agroindustry, wholesalers, shopkeepers, and hypermarkets. The Epsilon constraint method is used to solve the multi-objective model. A set of Pareto optimal solutions helped evaluate tradeoffs between the three objectives and find the location of collection and distribution centers. The proposed generic mathematical model is applicable to any food supply chain, as it allows for the improvement of the established performance measures and the distribution flows for the different echelons. The model considers the losses in perishable food from the impacts caused by changes in temperature (T0) and humidity level (RH) at different thermal floors of mountain ranges
