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Optimization approximations for capacity constrained material requirements planning
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DOI：10.1016/S0925-5273(02)00400-0.png)
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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. (C) 2002 Elsevier Science B.V. All rights reserved.
Keyword:
MRP
sequencing
rolling horizons
heuristic
setups
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