Simulation-Based Multi-Objective Optimization for Distributed Material Transportation System

 
 
 
  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract


    Material Transportation System (MTS) is required to move materials within a factory, warehouse, or other facilities. This study focused on AGV where the optimization of MTS is further studied. Although there is increasing demand in AGV control architecture, there is still unexplored potential in optimizing AGV performance measures. Applying AGVs in logistic factory may help in improving the efficiency in material flow and distribution among workstation at the right time and the right place. The aim of this study is to propose a simulation-based vehicle requirement analysis of AGVs in warehouse area with low mixed product variation. Simulations results show optimized number of AGV in warehouse area is achieved and succeed in produce short cycle time with high throughput.

     

     


  • Keywords


    AGV, Multi-objective optimization, Material transportation system, Extension Rule.

  • References


      [1] Anylogic Transportation Simulation. Retrieved from http://www.anylogic.com/transportation/

      [2] Cardarelli E. et al, 2015. Interacting with a Multi AGV System. Intelligent Computer Comunication and Processing (ICCP), IEEE Internatioanal Conference, pp. 263–267, 2015.

      [3] Caridá V. F., Jr O. M., and Tuma C. C. M., “Approaches of fuzzy systems applied to an AGV dispatching system in a FMS,” International Journal of Advanced Manufacturing Technology, vol. 79, Issue. 1, pp. 615-625, 2015.

      [4] Fauadi M. H. F. B. M., Lin H. and Murata T., “Dynamic task assignment of autonomous AGV system based on multi agent architecture,” 2010 IEEE International Conference on Progress in Informatics and Computing, Shanghai, 2010, pp. 1151-1156.

      [5] Fauadi M. H. F. B. M., Yahaya S. H. and Murata T., 2013. Intelligent combinatorial auctions of decentralized task assignment for AGV with multiple loading capacity. IEEJ Transactions on Electrical and Electronic Engineering, Volume 8, Issue 4, pp. 371–379, 2013. doi:10.1002/tee.21868.

      [6] Fauadi M. H. F. B. M., Li W. L. and Murata T., 2011. Combinatorial Auction Method for Decentralized Task Assignment of Multiple-Loading Capacity AGV Based on Intelligent Agent Architecture. 2011 IEEE Second International Conference on Innovations in Bio-inspired Computing and Applications, Shenzhen, pp. 207-211.

      [7] Fauadi M. H. F. B. M., Murata T.. 2010. Makespan Minimization of Machines and Automated Guided Vehicles Schedule Using Binary Particle Swarm Optimization. Proceedings of the International MultiConference of Engineers and Computer Scientists (IMECS) Volume 3 pp. 1897-1902.

      [8] Hodgson T. J. and King E., Developing Control Rules For An AGV using Markov Decision Process,” Proceedings of 24th Conference on Decision and Control, pp. 1817–1821, 1985.

      [9] Kaighobadi M., “Flexible Manufacturing Systems: An Overview,” International Journal of Operations & Production Management, vol. 14, Issues. 4, pp. 26-49, 1993.

      [10] Liu J., Wang Z., Xu Q., and Huang Q., “Path scheduling for multi-AGV system based on two-staged traffic scheduling scheme and genetic algorithm,” Journal of Computational Methods in Sciences and Engineering, vol. 15, Issue. 2, pp. 163–169, 2015.

      [11] Smolic-rocak N., Bogdan S., Kovacic Z., and Petrovic T., Time Windows Based Dynamic Routing in Multi-AGV Systems,” IEEE Trans on Automation Science and Engineering, vol. 7, Issue. 1, pp. 151–155, 2010.

      [12] Tseng Y., “The Role of Transportation in Logistics Chain,” Proceedings of the Eastern Asia Society for Transportation Studies, vol. 5, pp. 1657–1672, 2005.

      [13] Yifei T. Y. T., Junruo C. J. C., Meihong L. M. L., Xianxi L. X. L., and Yali F. Y. F., “An Estimate and Simulation Approach to Determining the Automated Guided Vehicle Fleet Size in FMS,” Comput. Sci. Inf. Technol. (ICCSIT), 2010 3rd IEEE Int. Conf., vol. 9, pp. 432–435, 2010.

      [14] Yu R., Guo H., and Chen H., “MPC-Based Regional Path Tracking Controller Design for Autonomous Ground Vehicles,” Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on, pp. 2510–2515, 2015.


 

View

Download

Article ID: 18987
 
DOI: 10.14419/ijet.v7i3.34.18987




Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.