DOI QR코드

DOI QR Code

Logistics Allocation and Monitoring System based on Map and GPS Information

Map과 GPS 기반의 혼적을 고려한 물류할당 및 모니터링 시스템

  • Park, Chulsoon (School of Industrial Engineering and Naval Architecture, Changwon National University) ;
  • Bajracharya, Larsson (Dept of Information & Communication Engineering, Changwon National University)
  • Received : 2018.11.13
  • Accepted : 2018.12.10
  • Published : 2018.12.31

Abstract

In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

Keywords

References

  1. Bent, R. and Van Hentenryck, P., A two-stage hybrid algorithm for pickup and delivery vehicle routing problems with time windows, Computers and Operations Research, 2006, Vol. 33, No. 4, pp. 875-893. https://doi.org/10.1016/j.cor.2004.08.001
  2. Dumas, Y., Desrosiers, J., and Soumis, F., The pickup and delivery problem with time windows, European Journal of Operational Research, 1991, Vol. 54, No. 1, pp. 7-22. https://doi.org/10.1016/0377-2217(91)90319-Q
  3. Ha, H.G. and Kim, Y.J., The strategies to stimulate online marketplaces for freight exchange services, [Sejong, Korea] : The Korea Transport Institute, 2003.
  4. IBM, IBM ILOG CPLEX Interactive Optimizer 12.8. 0.0, https://www.ibm.com/analytics/cplex-optimizer.
  5. Kang, C.S. and Lee, J.S., A Heuristic for Fleet Size and Mix Vehicle Routing Problem with Time Deadline, Journal of Society of Korea Industrial and Systems Engineering, 2005, Vol. 28, No. 2, pp. 8-17.
  6. Lau, H.C. and Liang, Z., Pickup and delivery with time windows : algorithms and test case generation, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence, 2001, pp. 333-340.
  7. Lee, S.C. and Yu, J.C., Improved VRP & GA-TSP Model for Multi-Logistics Center, Journal of the Korea Academia-Industrial Cooperation Society, 2007, Vol. 8, No. 5, pp. 1279-1288.
  8. Li, H. and Lim, A., A metaheuristic for the pickup and delivery problem with time windows, Proceedings 13th IEEE International Conference on Tools with Artificial Intelligence, 2001, pp. 160-170.
  9. Moon, G.J. and Hur, J.H., Development of an efficient vehicle routing heuristic by 2 Step advanced calculation, Journal of the Korean Institute of Plant Engineering, 2007, Vol. 12, No. 2, pp. 5-15.
  10. Moon, G.J. and Park, S.M., A Possible Heuristic for Variable Speed Vehicle Routing Problem with 4 Time Zone, Journal of society of Korea Industrial and Systems Engineering, 2012, Vol. 35, No. 4, pp. 171-178. https://doi.org/10.11627/jkise.2012.35.4.171
  11. Nanry, W.P. and Barnes, J., Solving the pickup and delivery problem with time windows using reactive tabu search, Transportation Research Part B Methodological, February 2000, Vol. 34, No. 2, pp. 107-121. https://doi.org/10.1016/S0191-2615(99)00016-8
  12. Ropke, S. and Pisinger, D., An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows, Transportation Science, 2006, Vol. 40, No. 4, pp. 455-472. https://doi.org/10.1287/trsc.1050.0135
  13. Savelsbergh, M.W.P. and Sol, M., The General Pickup and Delivery Problem, Transportation Science, 1995, Vol. 29, No. 1, pp. 17-29. https://doi.org/10.1287/trsc.29.1.17
  14. Sigurd, M.M., Pisinger, D., and Sig, M., The Pickup and Delivery Problem with Time Windows and Precedences, Transportation Science, 2004, Vol. 38, pp. 197-209. https://doi.org/10.1287/trsc.1030.0053
  15. SK Telecom, Tmap API, http://tmapapi.sktelecom/index.html.
  16. Xu, H., Chen, Z.L., Rajagopal, S., and Arunapuram, S., Solving a Practical Pickup and Delivery Problem, Transportation Science, 2003, Vol. 37, No. 3, pp. 347-364. https://doi.org/10.1287/trsc.37.3.347.16044