Optimization approximations for capacity constrained material requirements planning

Clark, Alistair R.

Abstract

This paper develops three mixed integer programming (MIP) models and solution methods to assist in identifying a capacity feasible master production schedule (MPS) in material requirements planning (MRP) systems. The initial exact model takes into account sequence-dependent setup times of both end-items and components, but is optimally solvable only for small product structures. A first approximate model and solution method, to be used with larger product structures, suboptimally schedules setups and lots on a period-by-period basis, estimating the capacity usage of future setups through the use of linear rather than integer variables. A second model and method, developed from the first, greatly accelerates computing time by sequencing setups gradually within each period, but again suboptimally. The trade-offs between schedule quality and computing time are analyzed in computational tests. The second model is able to schedule setups of up to 100 products on 10 machines over 5 periods in reasonable computing time. The tests show that this complex production scheduling problem can be practicably and successfully simplified both in terms of modelling and of solution method. © 2002 Elsevier Science B.V. All rights reserved.

Citation

Clark, A. R. (2003). Optimization approximations for capacity constrained material requirements planning. International Journal of Production Economics, 84(2), 115-131. https://doi.org/10.1016/S0925-5273%2802%2900400-0

• Journal Article Type: Article
• Publication Date: May 11, 2003
• Journal: International Journal of Production Economics
• Print ISSN: 0925-5273
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 84
• Issue: 2
• Pages: 115-131
• DOI: https://doi.org/10.1016/S0925-5273%2802%2900400-0
• Keywords: MRP, sequencing, rolling horizons, heuristic, setups
• Public URL: https://uwe-repository.worktribe.com/output/1070028
• Publisher URL: http://dx.doi.org/10.1016/S0925-5273(02)00400-0