Optimizing stochastic production-inventory systems: A heuristic based on simulation and regression analysis

Antonio Arreola-Risa, Víctor Giménez and José Luis Martínez-Parra

European Journal of Operational Research, 2011, vol. 213, issue 1, 107-118

Abstract: 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.

Keywords: Production; Inventory; Simulation; Regression; analysis; Supply-chain; management (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377-2217(11)00186-X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:213:y:2011:i:1:p:107-118

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().