Abstract—Nowadays increasing global and competitive marketplace requires more agile firm to survive and succeed. Therefore, the importance of integration for reverse logistics is growing for companies. Reverse logistical activities include return, remanufacture, disassemble and dispose of products can be quite complex to manage. In addition, demand can be difficult to predict and information flows quite challenging to process. These complexities have amplified the need for reengineering of existing reverse system. The purpose of this work is to propose an approach based on multi-agents system and semantic web technologies to efficiently integrate data and information in reverse logistics(RL) activities, and to reduce the uncertainty in the decision making process. Each agent execute different tasks in each step in reverse logistics Process, and each of them is able to take the best decisions, estimating benefits in cost and time, analyzing and managing uncertain information about return, using Bayesian decision network.

Index Terms—reverse logistics, multi-agents system, semantic-Web, decision-making, bayesian decision network

Cite: Fatima Lhafiane, Abdeltif Elbyed, and Mohamed Bouchoum, "Improving Reverse Logistics Process Using Multi-Agents System and Semantic Web," Journal of Traffic and Logistics Engineering, Vol. 2, No. 3, pp. 206-210, September 2014. doi: 10.12720/jtle.2.3.206-210