Meng Yu

Work place: College of Logistics Engineering, Wuhan University of Technology, Wuhan, P.R. China



Research Interests: Database Management System, Decision Support System, Combinatorial Optimization


Meng. Yu, female, was born in Wuhan, May 1975, received her BEng in Automatic Engineering in 1997 and MEng in Mechanical Engineering in 2000 from Wuhan Transportation University of Technology, China, and received PhD Degree in College of Logistics Engineering, Wuhan University of Technology, China.
Now she is an Associate Professor of Institute of Logistics Engineering, Wuhan University of Technology and is mainly engaged in the logistics system planning, system optimization and decision making, logistics system simulation, intelligent optimization of production scheduling research.

Author Articles
Multi-agent-based Fuzzy Dispatching for Trucks at Container Terminal

By Meng Yu Yanwei Zhang

DOI:, Pub. Date: 8 Dec. 2010

At container terminals, containers are transported from the marshalling yard to the quay and vice versa by Container Trucks (CTs). This study discusses how to dispatch CTs by utilizing information about pickup and delivery locations and time in future delivery tasks based on dynamic dispatching strategy in which multiple tasks are matched with multiple CTs. n this paper, Multi-agent system (MAS) is used as the basis for an intelligent dispatch system. To aim at that the characteristic of management of container terminal is how to optimize resource of terminal, the trends of decision-making way for management of container terminal, research and application of Multi-Agent system is summarized. Relationship between transport tasks and service of CTS has been taken as a contract net using the fuzzy set theory and method. Considering the load of communication and consultation efficiency in system, the bidirectional negotiation mechanism is adopted. The dispatching model based on Contract Network Protocol (CNP) using bidirectional negotiation is provided for assigning optimal delivery tasks to CTs and fuzzy reasoning process of dispatching decisions is suggested. The method has both virtues of precision of static planning and flexibility of CNP and has been confirmed by cases.

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