TY - JOUR
T1 - Optimizing stochastic production-inventory systems: A heuristic based on simulation and regression analysis
AU - Arreola-Risa, Antonio
AU - Giménez-García, Víctor M.
AU - Martínez-Parra, José Luis
PY - 2011/8/16
Y1 - 2011/8/16
N2 - We present a heuristic optimization method for stochastic production-inventory systems that defy analytical modelling and optimization. The proposed heuristic takes advantage of simulation while at the same time minimizes the impact of the dimensionality curse by using regression analysis. The heuristic was developed and tested for an oil and gas company, which decided to adopt the heuristic as the optimization method for a supply-chain design project. To explore the performance of the heuristic in general settings, we conducted a simulation experiment on 900 test problems. We found that the average cost error of using the proposed heuristic was reasonably low for practical applications. © 2011 Elsevier B.V. All rights reserved.
AB - We present a heuristic optimization method for stochastic production-inventory systems that defy analytical modelling and optimization. The proposed heuristic takes advantage of simulation while at the same time minimizes the impact of the dimensionality curse by using regression analysis. The heuristic was developed and tested for an oil and gas company, which decided to adopt the heuristic as the optimization method for a supply-chain design project. To explore the performance of the heuristic in general settings, we conducted a simulation experiment on 900 test problems. We found that the average cost error of using the proposed heuristic was reasonably low for practical applications. © 2011 Elsevier B.V. All rights reserved.
KW - Inventory
KW - Production
KW - Regression analysis
KW - Simulation
KW - Supply-chain management
U2 - 10.1016/j.ejor.2011.02.031
DO - 10.1016/j.ejor.2011.02.031
M3 - Article
SN - 0377-2217
VL - 213
SP - 107
EP - 118
JO - European Journal of Operational Research
JF - European Journal of Operational Research
ER -