Optimizing Food Bank Logistics: A synchronized Approach to Mobile Food Pantry Routing

Food insecurity is a global challenge affecting nations across different economic spectrums, from underdeveloped to developed regions. Food banks, driven by a humanitarian mission, strive to achieve a delicate balance between ensuring equitable distribution among areas in need and increasing the number of individuals served within the constraints of limited resources. This study introduces a Mixed Integer Programming (MIP) model specifically crafted to address the synchronized routing of Mobile Food Pantry Trucks (MFPTs) for food distribution. These MFPTs enable food banks to deliver food directly to those in need by dispatching their vehicles and personnel to locations where the demand is most significant. Our optimization approach places a substantial emphasis on minimizing routing, increasing effectiveness, and ensuring fair food allocation to the food-insecure population while reducing waste. We design a metaheuristic to solve large instances of the problem, conducting a numerical analysis using simulated data to showcase the efficacy of our proposed approach. Results indicate that our metaheuristic exhibits fast and efficient performance in terms of solution quality and computational time compared to the MIP solver.