A MIP based heuristic for capacitated MRP systems

Although Material Requirements Planning (MRP) is the most widely used production planning tool in today’s manufacturing companies, its inability to perform an exhaustive capacity planning, lack of a comprehensive and integrated shop floor extension and using constant and inflated lead times necessitate intelligent methods for developing cost effective production plans. A single optimization model might be employed to overcome these limitations, but it would be intractable to use it in large manufacturing systems. Hence, in this paper, we propose a heuristic method called Capacity Allocater and Scheduler, CAS, to eliminate drawbacks of MRP systems and provide solutions for large-scale instances. The CAS procedure, based on iteratively solving relaxed Mixed Integer Programming (MIP) models, is built on a lot sizing and scheduling framework, which considers both supply alternatives and lot size restrictions simultaneously. Finally, we give a detailed numerical example to demonstrate how CAS may be used in practice, and provide our concluding remarks.