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

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. 2011 Elsevier B.V. All rights reserved.

authors

• Arreola-Risa, Antonio

published proceedings

• EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

author list (cited authors)

• Arreola-Risa, A., Gimenez-Garcia, V. M., & Luis Martinez-Parra, J.

citation count

• 15

complete list of authors

• Arreola-Risa, Antonio||Gimenez-Garcia, Victor M||Luis Martinez-Parra, Jose

publication date

• January 2011

publisher

• Elsevier  Publisher

published in

• European Journal of Operational Research  Journal

keywords

• Inventory
• Production
• Regression Analysis
• Simulation
• Supply-chain Management

Digital Object Identifier (DOI)

• 10.1016/j.ejor.2011.02.031

start page

• 107

end page

• 118

volume

• 213

issue

• 1

URL

• http://dx.doi.org/10.1016/j.ejor.2011.02.031