Simulation-Based Optimization for Large-Scale Perishable Agri-Food Cold Chain in Rwanda: Agent-Based Modeling Approach

The global food supply chain faces significant challenges in maintaining the quality and safety of perishable agri-food products. This study introduces a novel approach to demonstrate the efficiency of using the perishable agri-food cold supply chain (FCC) by integrating optimization techniques and agent-based modeling (ABM) simulation. Addressing complexities and challenges such as precise temperature control, emission reduction, waste minimization, and finding the best implementation of cold chain infrastructure, the research applies ABM to model dynamic interactions within the FCC. By testing thousands of simulation scenarios in AnyLogic, the paper demonstrates how the proposed model can support strategic decision-making, demonstrate potential export levels, assess crop quality over time, and evaluate waste reduction compared to non-cold chain scenarios. The research further discusses the implementation of the proposed model in a real case study in Rwanda, Africa, showcasing its contribution to optimizing configuration, reducing food loss and CO2 emissions.