Multi-agent modeling and simulation for petroleum supply chain

Authors:
Jiang Tian;Huaglory Tianfield
Affiliations:
School of Computing and Mathematical Sciences, Glasgow Caledonian University, Glasgow, UK;School of Computing and Mathematical Sciences, Glasgow Caledonian University, Glasgow, UK
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent computing: Part II
Year:
2006

Citing 3
Cited 4

Introduction to Multiagent Systems

Introduction to Multiagent Systems
Scheduling the Supply Chain by Teams of Agents

HICSS '03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences (HICSS'03) - Track 3 - Volume 3
Coordinating multiple agents in the supply chain

WET-ICE '96 Proceedings of the 5th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE'96)

A study upon the architectures of multi-agent systems for petroleum supply chain

CDVE'07 Proceedings of the 4th international conference on Cooperative design, visualization, and engineering
Multi-agent based dynamic supply chain formation in semi-monopolized circumstance

ICIC'07 Proceedings of the intelligent computing 3rd international conference on Advanced intelligent computing theories and applications
Validating ambient intelligence based ubiquitous computing systems by means of artificial societies

Information Sciences: an International Journal
Testing context-aware services based on smartphones by agent based social simulation

Journal of Ambient Intelligence and Smart Environments - Intelligent agents in Ambient Intelligence and smart environments

Quantified Score

Hi-index	0.00

Visualization

Abstract

The petroleum supply chain is an old problem with new challenges. Multi-agent system has recognized as an effective methodology for supply chain management. This paper conducts a systematic multi-agent methodology to China petroleum supply chain system, where multi-agent models are constructed, and the multi-agent system is simulated in Zeus agent platform. Particularly, the advantages of multi-agent modeling and simulation in supply chain management are addressed and demonstrated.