Ozturk, CemalettinÖrnek, Mustafa Arslan2023-06-162023-06-1620120360-83521879-0550https://doi.org/10.1016/j.cie.2012.06.005https://hdl.handle.net/20.500.14365/1123Although 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. (C) 2012 Elsevier Ltd. All rights reserved.eninfo:eu-repo/semantics/closedAccessMulti-level capacitated lot-sizing problem with linked lots and backorders (MLCLPLB)Mathematical programmingHeuristicsDecompositionArticle10.1016/j.cie.2012.06.0052-s2.0-84868194760