A simulation-based optimization method for solving the integrated supply chain network design and inventory control problem under uncertainty

Wenhe Ye, Fengqi You*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

One of the key objectives of an optimised supply chain is to maintain a low operation cost as well as the service quality at a satisfactory level under demand uncertainty. However, the supply chain network design and inventory control optimisation are usually conducted in a sequential manner where the supply chain network is first determined by solving a mixed-integer programing (MIP) problem, and then the supply chain system with the given network design is tested as a "what if" problem in order to evaluate and improve its performance. Over the last decade, simulation modelling is regarded as an efficient tool for evaluating the performance of a real-world supply chain under different conditions and flexible control policies and simulation-based optimisation has been widely studied for solving inventory management problem under various uncertainties. In this work a hybrid computational framework is proposed to solve both the network design problem and the associated inventory control problem simultaneously. By incorporating region-wise metamodeling method to reduce the computation load, a multi-echelon supply chain case with 13 inventory stocking nodes can be solved within 3,621 s with the proposed algorithm. As a comparison, the simulation-based problem is also solved by the genetic algorithm (GA) toolbox in MATLAB, which only returns a 31 % higher cost after 13,844 s.

Original languageEnglish (US)
Title of host publicationChemical Engineering Transactions
PublisherItalian Association of Chemical Engineering - AIDIC
Pages499-504
Number of pages6
Volume45
ISBN (Electronic)9788895608365
DOIs
StatePublished - Oct 1 2015

ASJC Scopus subject areas

  • Chemical Engineering(all)

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    Ye, W., & You, F. (2015). A simulation-based optimization method for solving the integrated supply chain network design and inventory control problem under uncertainty. In Chemical Engineering Transactions (Vol. 45, pp. 499-504). Italian Association of Chemical Engineering - AIDIC. https://doi.org/10.3303/CET1545084