An Integrated Mixed-Integer Linear Programming–Simulation Framework for Network Design and Operations Optimization in Iraq’s Date-Fruit Supply Chain

Iraq's date-fruit supply chain faces persistent inefficiencies arising from a dispersed collection network, imbalanced processing capacity, and limited cold chain and logistics infrastructure.This paper proposes an optimized operational model of mixedinteger linear programming (MILP), constraint-based scheduling, and discrete-event simulation.The MILP model formulates the network structure of data collection and processing centers to optimize total logistics costs.The scheduling component generates feasible harvest and processing plans under perishability, labor availability, and capacity constraints.Simulation is used as a method of analyzing complex systems.The proposed models and simulation demonstrate a 42% and 28% reduction in data transportation distance and cost, respectively, and an improvement in facility utilization from 58% to 93%.The scheduling models demonstrate a 22% reduction in date harvesting and processing waiting time and an improvement of 26% in peak throughput.The simulation results demonstrate a 36.5% and 14.2% reduction in post-harvest date losses and an improvement in the shelf life of deluxe dates.