Title: Presenting a multi agent system for estimating risk in supply chain management

Authors: Leila Ahmadpour; Abolfazl Kazemi; Soroush Avakh Darestani

Addresses: Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran ' Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran ' Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract: Nowadays, supply chains play an inevitable role in prompt handling of varying customer's needs. Furthermore, with increasing emphasis on vulnerabilities in supply chains, effective mathematical tools for analysing and understanding appropriate supply chain risk evaluation are now attracting more attention. Administration of a successful supply chain depends on how efficiently of the network design is measured and how source risks effect it. This research has two objectives. The first one is to design a multi agent supply chain network that addresses an uncertain environment threatened by different risk sources in order to capture the real world conditions; the second one is to present a methodology for estimating risk in the proposed network. Moreover tree of scenarios are constructed and risk assessment model considering domino effect is built in order to carry out the overall quantitative risk assessment. Then, probability theories are applied in the quantitative method. In conclusion, the key benefits and experience gained from this study and further research opportunity are emphasised.

Keywords: risk estimation; multi agent system; supply chain management; domino effect.

DOI: 10.1504/IJSOM.2017.086312

International Journal of Services and Operations Management, 2017 Vol.28 No.2, pp.222 - 242

Received: 11 Nov 2015
Accepted: 04 Mar 2016

Published online: 04 Sep 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article