TY - JOUR
T1 - Capacity-constrained reorder intervals for materials requirements planning systems
AU - Hill, Arthur V.
AU - Raturi, Amitabh S.
AU - Sum, Chee Chuong
PY - 1997/1/1
Y1 - 1997/1/1
N2 - This paper develops a model for the reorder interval problem for general production systems with constant demand, multiple capacity constraints, commonality, non-instantaneous production, and non-nested reorder intervals. We present this model in the context of a materials requirements planning (MRP) system. Four simple greedy heuristics are presented to find solutions to the model. A six-factor experiment with 192 test problems is used to evaluate the heuristics. The factors in the experiment included the procedures, number of items, capacity tightness, degree of commonality, setup cost to carrying cost ratio, and setup time to run time ratio. For smaller problems the heuristics are compared with optimal solutions found with an exact branch-and-bound algorithm. For larger problems, the heuristics are compared with a lower bound. The results of the experiment show that the heuristics provide excellent solutions across all experimental factors. Computing times for the proposed heuristics appear to be practical even for realistic MRP environments with many thousands of items.
AB - This paper develops a model for the reorder interval problem for general production systems with constant demand, multiple capacity constraints, commonality, non-instantaneous production, and non-nested reorder intervals. We present this model in the context of a materials requirements planning (MRP) system. Four simple greedy heuristics are presented to find solutions to the model. A six-factor experiment with 192 test problems is used to evaluate the heuristics. The factors in the experiment included the procedures, number of items, capacity tightness, degree of commonality, setup cost to carrying cost ratio, and setup time to run time ratio. For smaller problems the heuristics are compared with optimal solutions found with an exact branch-and-bound algorithm. For larger problems, the heuristics are compared with a lower bound. The results of the experiment show that the heuristics provide excellent solutions across all experimental factors. Computing times for the proposed heuristics appear to be practical even for realistic MRP environments with many thousands of items.
UR - http://www.scopus.com/inward/record.url?scp=0031275499&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0031275499&partnerID=8YFLogxK
U2 - 10.1080/07408179708966414
DO - 10.1080/07408179708966414
M3 - Article
AN - SCOPUS:0031275499
SN - 0740-817X
VL - 29
SP - 951
EP - 963
JO - IIE Transactions (Institute of Industrial Engineers)
JF - IIE Transactions (Institute of Industrial Engineers)
IS - 11
ER -