An Application Oriented Multi-Agent Based Approach to Dynamic Truck Scheduling at Cross-Dock

Truck arrival management forms a very active stream of research and a crucial challenge for a cross-dock terminals. The study focuses on the truck congestion problem, which leads to a lower operation efficiency and a longer waiting time at the gate and at the yard. One of the operational measures to solve this problem is the truck appointment system. It is used to coordinate the major cross-dock planning activities and to regulate the arrival time of trucks at the cross-dock. When the trucker get an appointment time different to its preference time, then we are talking about a truck deviation time. Because the deviation will result in daily operations schedule, an optimization model for truck appointment was proposed in this paper. In the model, the truck deviation time was minimized subject to the constraints of resources availability including dock doors, yard zones, gate lanes, workforce and material handling systems. To solve the model, a method based multi-agent system to real-time truck scheduling, that take into account the uncertainty of arrival time as an operational characteristic, was designed. It ensures a negotiation among truck agents and resource agents. Lastly, a numerical experiments are provided to illustrate the validity of the model and to illustrate the working and benefit of our approach.

[1]  Amelia C. Regan,et al.  Real-Time Trailer Scheduling for Crossdock Operations , 2008, Transportation Journal.

[2]  Dirk Cattrysse,et al.  Cross-docking: State of the art , 2012 .

[3]  Nils Boysen,et al.  Jena Research Papers in Business and Economics Scheduling Inbound and Outbound Trucks at Cross Docking Terminals , 2007 .

[4]  Anne-Laure Ladier Planification des opérations de cross-docking : prise en compte des incertitudes opérationelles et de la capacité des ressources internes , 2014 .

[5]  Satoru Araki FIPA ACL Message Structure Specification , 2000 .

[6]  Wooyeon Yu,et al.  Operational strategies for cross docking systems , 2002 .

[7]  Jacques Ferber,et al.  Les Systèmes multi-agents: vers une intelligence collective , 1995 .

[8]  Wei He,et al.  A solution for cross-docking operations planning, scheduling and coordination , 2008, 2008 IEEE International Conference on Service Operations and Logistics, and Informatics.

[9]  M. Zandieh,et al.  A multi-criteria cross-docking scheduling with just-in-time approach , 2010 .

[10]  Nathan Huynh,et al.  Robust Scheduling of Truck Arrivals at Marine Container Terminals , 2008 .

[11]  Pei-Chann Chang,et al.  Simultaneous dock assignment and sequencing of inbound trucks under a fixed outbound truck schedule in multi-door cross docking operations , 2013 .

[12]  Alain Cardon Modéliser et concevoir une machine pensante : approche de la conscience artificielle , 2004 .

[13]  Bernard Penz,et al.  Scheduling cross docking operations under full, partial and no information on inbound arrivals , 2011, Comput. Oper. Res..

[14]  Feng Chen,et al.  Minimizing makespan in two-stage hybrid cross docking scheduling problem , 2009, Comput. Oper. Res..

[15]  William A. Woods,et al.  Computational Linguistics Transition Network Grammars for Natural Language Analysis , 2022 .

[16]  Adil Baykasoglu,et al.  An application oriented multi-agent based approach to dynamic load/truck planning , 2015, Expert Syst. Appl..

[17]  George F. List,et al.  Using time-varying tolls to optimize truck arrivals at ports , 2011 .

[18]  Jian Yang,et al.  Real-Time Multivehicle Truckload Pickup and Delivery Problems , 2004, Transp. Sci..