Simulation-based method for optimizing multi-echelon inventory systems

Yunfei Chu, Fengqi You*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We propose a novel simulation-based optimization framework for optimizing distribution inventory systems where each facility is operated with the (r, Q) inventory policy. The objective is to minimize the inventory cost while maintaining acceptable service levels quantified by the fill rates. The inventory system is modeled and simulated by an agent-based system, which returns the performance functions. The expectations of these functions are then estimated by the Monte-Carlo method. Then the optimization problem is solved by a cutting plane algorithm. As the black-box functions returned by the Monte-Carlo method contain noises, statistical hypothesis tests are conducted in the iteration. A local optimal solution is obtained if it passes the test on the optimality conditions.

Original languageEnglish (US)
Article number7039675
Pages (from-to)1899-1904
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2015-February
Issue numberFebruary
DOIs
StatePublished - Jan 1 2014

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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