Operations, Information and Decisions Papers

Document Type

Journal Article

Date of this Version

7-2002

Publication Source

Decision Support Systems

Volume

33

Issue

3

Start Page

323

Last Page

333

DOI

10.1016/S0167-9236(02)00019-2

Abstract

We model an electronic supply chain managed by artificial agents. We investigate whether artificial agents do better than humans when playing the MIT Beer Game. Can the artificial agents discover good and effective business strategies in supply chains both in stationary and non-stationary environments? Can the artificial agents discover policies that mitigate the Bullwhip effect? In particular, we study the following questions: Can agents learn reasonably good policies in the face of deterministic demand with fixed lead time? Can agents cope reasonably well in the face of stochastic demand with stochastic lead time? Can agents learn and adapt in various contexts to play the game? Can agents cooperate across the supply chain?

Copyright/Permission Statement

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

artificial agents, automated supply chains, beer game, bullwhip effect, genetic algorithms

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Date Posted: 27 November 2017

This document has been peer reviewed.