Cross-platform software system for the logistics of humanitarian services

2023;
: pp. 79 - 88
1
Lviv Politecnic National University
2
Lviv Polytechnic National University, Computer Engineering Department

The problem of designing a cross-platform software system for the logistics of humanitarian services is considered. Existing software analogs of international deliveries are considered. A comparison of popular software products in the field of international trade is given.

The technologies for developing software services to ensure the cross-platform system for the logistics of humanitarian services are reviewed.

The algorithms used in the system for solving the transportation problem, namely the routing problem, are presented, with the help of which the most optimal path between the supply points is selected.

The general algorithm of the system operation is proposed and the structural diagram of the application is presented.

  1. Bloch, J. (2018). Effective Java: A Tutorial. 3rd ed. Upper Saddle River, NJ: Addison-Wesley. 901 p. DOI: 10.1145/2185359.2185361.
  2. Walls, C. (2018). Spring in Action: A Tutorial. Shelter Island, NY: Manning Publications Co. 500 p. DOI: 10.1145/3174280.3174282.
  3. Chen, C., Xu, Y., Chen, X., Luo, X., & Wang, W. (2021). Java Virtual Machine: A Survey. ACM Computing Surveys, 54(3), 1-38. DOI: 10.1145/3456553.
  4. Al-Khayyal, M. A., Birch, D. M. T., & Hassan, M. B. M. E. (2014). A review of truck dispatching problems and solution approaches. Transportation Research Part B: Methodological, 66, 1-34. DOI: 10.1016/j.trb.2014.07.002.
  5. Olli Bräysy and Michel Gendreau. (2005). Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms. Transportation Science, 39(1):104–118. DOI: 10.1287/trsc.1030.0056
  6. Gendreau, M., Laporte, G., & Séguin, R. (1996). Stochastic vehicle routing. European Journal of Operational Research, 88(1), 3-12. DOI: 10.1016/0377-2217(95)00090-3.
  7. Shmoys, D. B., & Tardos, É. (2000). Network flows and graph algorithms. In Handbook of Discrete and Computational Geometry (pp. 609-655). CRC Press. DOI: 10.1007/3-540-36484-0_19.
  8. Simonis, H. (2006). Constraint applications in networks. In F. Rossi, P. van Beek, & T. Walsh (Eds.), Handbook of Constraint Programming (Vol. 2, pp. 875-903). Elsevier. DOI: 10.1016/S1361-8608(05)00062-
  9. Dechter, R. (2003). Constraint processing. Morgan Kaufmann. DOI: 10.1016/B978-1-55860-890-X5000-2.
  10. Carsten. J. Drexl, A. (1995). A Comparison of Constraint and Mixed-Integer Programming Solvers for Batch Sequencing with Sequence Dependent Setups. ORSA Journal on computing, 7(2):160–165. DOI: 10.1287/ijoc.7.2.160
  11. Holub, P., Liška, M., Rudová, H., & Troubil, P. (2010). "Comparison of CP and IP Techniques for Data Transfer Planning." In 28th Workshop of the UK Special Interest Group on Planning and Scheduling, pages 69-70. ISBN 978-88-904924-1-9
  12. Dantzig, G. B. (1951). Maximization of a linear function of variables subject to linear inequalities. In T. C. Koopmans (Ed.), Activity Analysis of Production and Allocation (pp. 339-347). Wiley & Chapman-Hall. ISBN: 978- 0471387594.
  13. Achterberg, T. (2007). "Constraint Integer Programming." Doctoral thesis, Technische Universität Berlin. DOI: 10.1007/978-3-540-68155-7.
  14. Fowler, M. (2014). SOLID Principles: An Introduction. MartinFowler.com. DOI: 10.1145/2531701.2531703.
  15. Freeman, E., Robson, E., Bates, B., & Sierra, K. (2014). Head First Design Patterns (1st ed.). O’Reilly. 867 p. ISBN: 978-0-596-00712-4.
  16. Achterberg, T., Berthold, T., Koch, T., & Wolter, K. (2008). "Constraint Integer Programming: A New Approach to Integrate CP and MIP." In: "Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems," Volume 01, pages 6-20. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3- 540-68155-7_4.
  17. Perron, L. (2011). "Operations Research and Constraint Programming at Google." In: "Principles and Practice of Constraint Programming – CP 2011," p. 2. Publisher: Springer, Berlin Heidelberg. DOI: 10.1007/978-3- 642-23786-7_1
  18. Mittelmann, H. (2014). Mixed Integer Linear Programming Benchmark (MIPLIB2010). [online] Available at: <http://plato.asu.edu/ftp/milpc.html>.
  19. Tuláček, M. (2014). Algorithms for automated logistics. Bc. Michal Tuláček Algorithms for automated logistics. http://www.tulacek.eu/mgr_thesis/thesis.pdf. DOI: 10.1145/2531701.2531703.
  20. Molodid, O. K. (2018). The transportation problem. (Electronic resource). Kyiv, Ukraine: Igor Sikorsky Kyiv Polytechnic Institute. DOI: 10.13140/RG.2.2.27260.79842
  21. Podotyaka, O. O., & Podotyaka, O. M. (2021). Solving a bicriteria transportation problem based on block normalization of criteria. Bulletin of Kharkiv National Automobile and Highway University, 92(1), 60. DOI:10.30977/BUL.2219-5548.2021.92.1.60