This study presents an optimization-based decision-support framework for ready-mix concrete (RMC) production and delivery scheduling in Qatar. A Mixed-Integer Linear Programming (MILP) model, implemented in IBM ILOG CPLEX Optimization Studio, is developed to address the operational complexity of coordinating batching, loading, transportation, and delivery activities under real-world constraints. The proposed approach supports a transition from semi-manual, experience-driven planning to a systematic, model-based optimization methodology.
The model explicitly incorporates Ministry of Interior (MOI) traffic restrictions, truck availability, plant loading capacities, delivery time windows, and route limitations. To enhance computational efficiency and practical applicability, a multi-stage heuristic optimization approach is integrated with the MILP formulation. The objective is to minimize deviations between requested and actual delivery times while ensuring schedules that are feasible and reliable.
Computational results demonstrate that the proposed framework achieves minimal delivery-time deviations, with most discrepancies occurring as early arrivals rather than delays. These results confirm the model's effectiveness in improving schedule reliability, optimizing resource utilization, and enhancing coordination between production and transportation operations. Overall, the study provides a robust optimization framework that supports more efficient and timely RMC delivery processes, offering practical value to the Qatari construction industry and similar urban environments with traffic constraints.