TY - GEN
T1 - On the use of Simheuristics to Optimize Safety-Stock Levels in Material Requirements Planning with Random Demands
AU - Barrios, Barry B.
AU - Juan, Angel A.
AU - Panadero, Javier
AU - Altendorfer, Klaus
AU - Peirleitner, Andreas J.
AU - Estrada-Moreno, Alejandro
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12/14
Y1 - 2020/12/14
N2 - Material requirements planning (MRP) integrates the planning of production, scheduling, and inventory activities in a manufacturing process. Many approaches to MRP management focus either on the simulation of the system (without considering optimization aspects) or in its optimization (without considering stochastic aspects). This paper analyzes a MRP version in which the demand of final products in each period is a random variable. The goal is then to find the optimal safety-stock configuration of both the product and the parts, i.e.: the configuration that minimizes the expected total cost. This total cost is given by: (i) the inventory cost; and (ii) a penalty cost generated by the occurrence of stock outs. To solve this stochastic optimization problem, a spreadsheet simulation model is proposed and a heuristic procedure is employed over it. A numerical example illustrates the main concepts of the proposed approach as well as its potential.
AB - Material requirements planning (MRP) integrates the planning of production, scheduling, and inventory activities in a manufacturing process. Many approaches to MRP management focus either on the simulation of the system (without considering optimization aspects) or in its optimization (without considering stochastic aspects). This paper analyzes a MRP version in which the demand of final products in each period is a random variable. The goal is then to find the optimal safety-stock configuration of both the product and the parts, i.e.: the configuration that minimizes the expected total cost. This total cost is given by: (i) the inventory cost; and (ii) a penalty cost generated by the occurrence of stock outs. To solve this stochastic optimization problem, a spreadsheet simulation model is proposed and a heuristic procedure is employed over it. A numerical example illustrates the main concepts of the proposed approach as well as its potential.
UR - http://www.scopus.com/inward/record.url?scp=85103916860&partnerID=8YFLogxK
U2 - 10.1109/WSC48552.2020.9383988
DO - 10.1109/WSC48552.2020.9383988
M3 - Conference contribution
AN - SCOPUS:85103916860
T3 - Proceedings - Winter Simulation Conference
SP - 1539
EP - 1550
BT - Proceedings of the 2020 Winter Simulation Conference, WSC 2020
A2 - Bae, K.-H.
A2 - Feng, B.
A2 - Kim, S.
A2 - Lazarova-Molnar, S.
A2 - Zheng, Z.
A2 - Roeder, T.
A2 - Thiesing, R.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Winter Simulation Conference, WSC 2020
Y2 - 14 December 2020 through 18 December 2020
ER -