This chapter considers the importance of decision support systems for supply chain risk management (SCRM). The first part provides an overview of the different operations research techniques and methodologies for decision making for managing risks, focusing on multiple-criteria decision analysis methods and mathematical programming. The second part is devoted to artificial intelligence (AI) techniques which have been applied in the SCRM domain to analyse data and make decisions regarding possible risks. These include Petri nets, multi-agent systems, automated reasoning and machine learning. The chapter concludes with a discussion of potential ways in which future decision support systems for SCRM can benefit from recent advances in AI research.
|Title of host publication||Revisiting Supply Chain Risk|
|Editors||George A. Zsidisin, Michael Henke|
|Number of pages||19|
|Volume||SSSCM, volume 7|
|Publication status||Published - 1 Jan 2019|
|Name||Springer Series in Supply Chain Management|