International Journal of Control, Automation, and Systems

Institute of Control, Robotics and Systems (제어로봇시스템학회)
권호 표지

Routing of Linear Motor based Shuttle Cars in the Agile Port Terminal with Constrained Dynamic Programming

  • Cho, Hyun-Cheol (Dept. of Electrical Engineering, Dong-A University) ;
  • Lee, Jin-Woo (Dept. of Electrical Engineering, Dong-A University) ;
  • Lee, Young-Jin (Dept. of Avionics Electrical Eng., Korea Aviation Polytechnic) ;
  • Lee, Kwon-Soon (Dept. of Electrical Engineering, Dong-A University)
  • Published : 2008.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

Linear motor (LM) based shuttle cars will play an important role in the future transportation systems of marine terminals to cope with increasing container flows. These systems are known as agile port terminals because of their significant advantages. However, routing for multiple shuttle cars is still an open issue. We present a network model of a container yard and propose constrained dynamic programming (DP) for its routing strategy with collision avoidance. The algorithm is a modified version of typical DP which is used to find an optimal path for a single traveler. We evaluate the new algorithm through simulation results for three shuttle cars in a mesh-type container yard.

Keywords

References

  1. P. Ioannou, E. Kosmatopoulos, H. Jula, A. Collinge, C. Liu, and A. Asef-Vaziri, "Cargo handling technologies," Technical Report, Univ. of Southern California, 2000
  2. M. Soylu, N. Ozdemirel, and S. Kayaligil, "A self-organizing neural network approach for the single AGV routing problem," European Journal of Operational Research, vol. 121, pp. 124-137, 2000 https://doi.org/10.1016/S0377-2217(99)00032-6
  3. S. Arora, A. Raina, and A. Mittal, "Collision avoidance among AGVs at junction," Proc. of the IEEE Intelligent Vehicles Symposium, pp. 585-589, 2000
  4. M. Konishi, T. Nishi, K. Nakano, and K. Sotobayashi, "Evolutionary routing method for multi mobile robots in transportation," Proc. of the IEEE Int. Symposium on Intelligent Control, pp. 490-495, 2002
  5. M. Dorigo, V. Maniezzo, and A. Colorni, "Ant system: Optimization by a colony of cooperating agents," IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 26, no. 1, pp. 29-41, 1996 https://doi.org/10.1109/3477.484436
  6. M. Norman, "A recursive method for traffic management through a complex path network," Proc. of the Simulation Conf., pp. 537-541, 2002
  7. G. Desaulniers, A. Langevin, D. Riopel, and B. Villeneuve, "Dispatching and conflict-free routing of automated guided vehicles: An exact approach," The Int. Journal of Flexible Manufacturing systems, vol. 15, pp. 309-331, 2003 https://doi.org/10.1023/B:FLEX.0000036032.41757.3d
  8. N. Wu and M. Zhou, "Modeling and deadlock control of automated guided vehicle systems," IEEE/ASME Trans. on Mechatronics, vol. 9, no. 1, pp. 50-87, 2004 https://doi.org/10.1109/TMECH.2004.823875
  9. J.-W. Yoo, E.-S. Sim, C. Cao, and J.-W. Park, "An algorithm for deadlock avoidance in an AGV system," International Journal of Advanced Manufacturing Technology, vol. 26, pp. 659-668, 2005 https://doi.org/10.1007/s00170-003-2020-4
  10. W. Winston, Operations Research, Duxbury, Belmont, 1994
  11. P. Ioannou, H. Jula, C. Liu, K. Vukadinovic, and H. Pourmohammadi, "Advanced material handling: automated guided vehicles in Agile ports," Technical Report, Center for advanced Transportation Technologies, University of Southern California, 2000