Soft evaluation of Boolean search queries in information retrieval systems
Information Technology Research Development Applications
Industrial and practical applications of DAI
Multiagent systems
The TREC robust retrieval track
ACM SIGIR Forum
MAGENTA technology: multi-agent systems for industrial logistics
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
A dynamic logistics process knowledge-based system - An RFID multi-agent approach
Knowledge-Based Systems
Argumentation-Based Inference and Decision Making--A Medical Perspective
IEEE Intelligent Systems
Decentralized supply chain planning framework for third party logistics partnership
Computers and Industrial Engineering
Agent-based negotiation and decision making for dynamic supply chain formation
Engineering Applications of Artificial Intelligence
A multi-agent platform for auction-based allocation of loads in transportation logistics
Expert Systems with Applications: An International Journal
A multi-agent approach to load consolidation in transportation
Advances in Engineering Software
Agent-based flight planning system for enhancing the competitiveness of the air cargo industry
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This paper advocates the use of multi-agent systems in the freight forwarding industry. We propose an intelligent mobile agent system to cope with a dynamic freight forwarding environment where up-to-date information is crucial but time-consuming to obtain. A key component of our system is an agent argumentation mechanism that allows decision support agents to discuss, argue, and come to a compromise in order to derive well-explained freight planning solutions. A number of artificial intelligence mechanisms are implemented, namely: (1) a mobile-agent-based automated information gathering mechanism, where designated mobile agents access various websites automatically to gather information (e.g., weather conditions on a candidate route) critical for cargo consolidation and route planning, (2) a fuzzy logics engine for risk evaluation, and (3) a simulated annealing engine for optimizing cargo consolidation. A system prototype is developed and the feasibility of our approach is demonstrated in a case study. A series of experiments are also conducted to evaluate the system's performance.