Abstract

The growth in the number of logistics platforms served by road, rail, waterway, and sea is a logical consequence of the extensive and rapid development of merchandise trade in a globalized economy. Transport and logistics are part of the same activity chain that allows goods to be transported to their destination. Dependent on the requirements of their customers and suppliers and subject to strong competition, companies in this sector must manage challenges concerning deadlines, flexibility, and diversity of goods, while handling other risks associated with transport and logistics. The Bayesian approach, proposed in this paper, covers all the steps necessary to implement decision support solutions for risk management and control, starting from the identification of risks and the preparation of intervention to the conducting of various operations in crisis In this work, the prediction and the control of the road risks are conducted using the influence diagram method, whose final objective is the optimization of the logistics function. After identifying and analyzing the different risks, the Bayesian networks (BNs) are initially used to model these risks and to prevent the various challenging situations from taking place in the logistics chain. As a second step, we use the influence diagram as a tool for the decision-making procedure. Finally, a case study is presented to highlight the substantial contribution of this tool to controlling road risks while transporting goods.

Information

Item Type:	Journal
Divisions:	» Faculty of Science and Technology
ePrint ID:	1233
Date Deposited:	2018-04-27
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/1233

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