A Robust Optimizing Reverse Logistics Model for Beef Products Using Multi Depot Vehicle Routing Problem

Beef is a perishable product and requires special handling. Demand for beef also fluctuates quite high heavily influenced by various religious events traditions in Indonesia. Under these conditions, reasons, products are returned from customers to distributors. An increase the number of leads costs risk damage. The research created an optimization model distribution recall with minimal risks. applied clustering method using Density-Based Spatial Clustering (DBSCAN) algorithm determine density customers’ locations orders. Optimization distance withdrawal Multi Depot Vehicle Routing Problem (MDVRP) Mixed Integer Linear Programming (MILP) mathematical modeling. results indicate three customer clusters one noise, most potential cluster 1. From this condition, delivery based on shipments two central warehouses. uses MDVRP MILP make company-owned trucks more profitable at rental truck replacement costs. produces robust changes capacity sensitivity analysis.