Designing Distribution Network for Indian Agri-fresh Food Supply Chain

Abstract

AbstractIn India, 85% of farmers have less than two hectares farming land. These farmers transport their products exclusively in the market to sell them in traditional Indian agri-fresh food supply chain. Owing to this, a higher transportation cost occurs in the traditional chain, which leads to low profitability of farmers. We propose aggregate product movement using clustering of farmers (based on the maximum distance traveled by a farmer) to achieve economy in transportation. A multi-period mixed-integer nonlinear programming (MINLP) model for multi-product is formulated of a four-echelon supply chain to minimize total distribution cost. The model determines location–allocation of farmers’ cluster centers and hubs, and product flow between facilities and inventory levels at hubs. The formulated model is transformed into a mixed-integer linear programming (MILP) model to handle large-size data. To check the validity and viability of the developed models, a real case study of Mandsaur district (India) is considered with small, medium, and large sizes of the problem. We compare the outcomes of both models obtained using LINGO 12.0 for small- and medium-size problems. It is reported that the MILP model is better than MINLP in terms of objective value and computational time. Furthermore, the results and dynamics in terms of farmers’ cluster formation for the MILP model on a large-size problem are discussed. The sensitivity analysis reports that the proposed MILP model is robust in terms of maximum distance traveled by a farmer to the total distribution cost.KeywordsAgri-fresh food supply chain (AFSC)Distribution network designMixed-integer nonlinear programming (MINLP)Mixed-integer linear programming (MILP)Clustering of farmers