SCHEDULING SINGLE-LOAD AND MULTI-LOAD AGVS IN CONTAINER TERMINALS

I n this paper, three solutions for scheduling problem of the Single-Load and Multi-Load Automated Guided Vehicles (AGVs) in Container Terminals are proposed. The problem is formulated as Constraint Satisfaction and Optimization. When capacity of the vehicles is one container, the problem is a minimum cost flow model. This model is solved by the highest performance Algorithm, i.e. Network Simplex Algorithm (NSA). If the capacity of the AGVs increases, the problem is a NP-hard problem. This problem has a huge search space and is tackled by the Simulated Annealing Method (SAM). Three approaches for its initial solution and a neighborhood function to the search method are implemented. The third solution is a hybrid of SAM and NSA. This hybrid is applied to the Heterogeneous AGVs scheduling problem in container terminals. Several the same random problems are generated, solved by SAM with the proposed approaches and the simulation results are compared. The experimental results show that NSA provides a good initial solution for SAM when the capacity of AGVs is heterogeneous.

[1]  Wen-Chyuan Chiang,et al.  Simulated annealing metaheuristics for the vehicle routing problem with time windows , 1996, Ann. Oper. Res..

[2]  Torsten Reiners,et al.  Vehicle dispatching at seaport container terminals using evolutionary algorithms , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[3]  Edward Tsang Scheduling techniques: a comparative study , 1995 .

[4]  Chung-Piaw Teo,et al.  Dispatching Automated Guided Vehicles in a Container Terminal , 2005 .

[5]  Hock Chan Sen Dynamic AGV-Container Job Deployment Strategy , 2002 .

[6]  Hironao Kawashima,et al.  A HEURISTIC APPROACH BASED ON THE STRING MODEL TO SOLVE VEHICLE ROUTING PROBLEM WITH BACKHAULS , 1998 .

[7]  Ling Qiu,et al.  Scheduling and routing algorithms for AGVs: A survey , 2002 .

[8]  B. Comm,et al.  The Minimum Cost Flow Problem and The Network Simplex Solution Method , 2003 .

[9]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[10]  B J Wook,et al.  A POOLED DISPATCHING STRATEGY FOR AUTOMATED GUIDED VEHICLES IN PORT CONTAINER TERMINALS , 2000 .

[11]  Katta G. Murty,et al.  A decision support system for operations in a container terminal , 2005, Decis. Support Syst..

[12]  C. Y. Leong SIMULATION STUDY OF A DYNAMIC AGV-CONTAINER JOB DEPLOYMENT SCHEME , 2000 .

[13]  Michael Florian,et al.  AN EFFICIENT IMPLEMENTATION OF THE NETWORK SIMPLEX METHOD. , 1997 .

[14]  Albert P. M. Wagelmans,et al.  Effective algorithms for integrated scheduling of handling equipment at automated container terminals , 2001 .

[15]  Matthias Lehmann,et al.  Dispatching multi-load AGVs in highly automated seaport container terminals , 2004, OR Spectr..

[16]  Albert P. M. Wagelmans,et al.  DYNAMIC SCHEDULING OF HANDLING EQUIPMENT AT AUTOMATED CONTAINER TERMINALS , 2001 .

[17]  Zbigniew J. Czech,et al.  Parallel simulated annealing for the vehicle routing problem with time windows , 2002, Proceedings 10th Euromicro Workshop on Parallel, Distributed and Network-based Processing.

[18]  Ling Qiu,et al.  A bi-directional path layout for conflict-free routing of AGVs , 2001 .

[19]  Hassan Rashidi,et al.  APPLYING THE EXTENDED NETWORK SIMPLEX ALGORITHM AND A GREEDY SEARCH METHOD TO AUTOMATED GUIDED VEHICLE SCHEDULING , 2005 .

[20]  Allan Larsen,et al.  The Dynamic Vehicle Routing Problem , 2000 .

[21]  Ling Qiu,et al.  Continuous scheduling of AGVs in a mesh-like path topology , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).