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Reseach Article

Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain

by Salma Mouatassim, Mustapha Ahlaqqach, Jamal Benhra, My Ali El Oualidi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 15
Year of Publication: 2016
Authors: Salma Mouatassim, Mustapha Ahlaqqach, Jamal Benhra, My Ali El Oualidi
10.5120/ijca2016910910

Salma Mouatassim, Mustapha Ahlaqqach, Jamal Benhra, My Ali El Oualidi . Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain. International Journal of Computer Applications. 145, 15 ( Jul 2016), 37-48. DOI=10.5120/ijca2016910910

@article{ 10.5120/ijca2016910910,
author = { Salma Mouatassim, Mustapha Ahlaqqach, Jamal Benhra, My Ali El Oualidi },
title = { Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 15 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 37-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number15/25358-2016910910/ },
doi = { 10.5120/ijca2016910910 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:59.066636+05:30
%A Salma Mouatassim
%A Mustapha Ahlaqqach
%A Jamal Benhra
%A My Ali El Oualidi
%T Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 15
%P 37-48
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Several researches have been done to optimize different flows in blood supply chain. However, the use of game theory in this sense is rare. The following work focus on the case of Morocco, consisting of 16 Regional Blood Transfusion Centers (RBTC) centralized around a National Blood Transfusion and Hematology Center (NBTHC). An approach based on hybridized game theory is adopted to form core and strongly stable coalitions and optimize as much as possible the transport cost. Firstly, the optimal cost of each coalition of the 33 possible coalitions; that the Director of NBTHC validated; is computed by using a mixed integer linear Programming model (MILP). Then these costs are introduced as data of two other MILP to define which structure minimizes the total cost allocated to each RTBC while maintaining core stability, in the case of the first MILP, and strong equilibrium in the case of the second. The VRPPDTW is also introduced within each coalition in order to optimize the cost of transport more.

References
  1. R. Aumann, “Acceptable points in general cooperative n-person Games,” Contrib. to Theory Games, vol. 40, pp. 287–324, 1959.
  2. M. Shubik, “Incentives, decentralized control, the assignment of joint costs and internal pricing,” Manage. Sci., 1962.
  3. M. Shubik, “Game theory and operations research: some musings 50 years later,” Oper. Res., 2002.
  4. A. V. Smirnov, L. B. Sheremetov, N. Chilov, and J. R. Cortes, “Soft-computing technologies for configuration of cooperative supply chain,” Appl. Soft Comput. J., vol. 4, no. 1, pp. 87–107, 2004.
  5. M. Jin and S. D. Wu, “Supplier coalitions in on-line reverse auctions: Validity requirements and profit distribution scheme,” Int. J. Prod. Econ., vol. 100, no. 2, pp. 183–194, 2006.
  6. S. L. Charles and D. R. Hansen, “An evaluation of activity-based costing and functional-based costing: A game-theoretic approach,” Int. J. Prod. Econ., vol. 113, no. 1, pp. 282–296, 2008.
  7. J. Drechsel and A. Kimms, “Computing core allocations in cooperative games with an application to cooperative procurement,” Int. J. Prod. Econ., vol. 128, no. 1, pp. 310–321, 2010.
  8. M. Nagarajan and G. Sošic, “Coalition stability in assembly models,” Oper. Res., 2009.
  9. M. Nagarajan and Y. Bassok, “A bargaining framework in supply chains: The assembly problem,” Manage. Sci., 2008.
  10. G. Reinhardt and M. Dada, “Allocating the gains from resource pooling with the Shapley value,” J. Oper. Res., 2005.
  11. G. Sošic, “Transshipment of inventories among retailers: Myopic vs. farsighted stability,” Manage. Sci., 2006.
  12. X. Chen, “Inventory Centralization Games with Price-Dependent Demand and Quantity Discount,” Oper. Res., vol. 57, no. 6, pp. 1394–1406, Dec. 2009.
  13. U. Özen, J. Fransoo, and H. Norde, “Cooperation between multiple newsvendors with warehouses,” Manuf. Serv., 2008.
  14. M. Frisk, M. Göthe-Lundgren, K. Jörnsten, and M. Rönnqvist, “Cost allocation in collaborative forest transportation,” Eur. J. Oper. Res., vol. 205, no. 2, pp. 448–458, 2010.
  15. S. Lozano, P. Moreno, B. Adenso-Díaz, and E. Algaba, “Cooperative game theory approach to allocating benefits of horizontal cooperation,” Eur. J. Oper. Res., vol. 229, no. 2, pp. 444–452, 2013.
  16. M. Guajardo and M. R??nnqvist, “Operations research models for coalition structure in collaborative logistics,” Eur. J. Oper. Res., vol. 240, no. 1, pp. 147–159, 2015.
  17. S. D’Amours and M. Rönnqvist, “Issues in Collaborative Logistics,” Springer Berlin Heidelberg, 2010, pp. 395–409.
  18. Bennis, “Apport de la modélisation , optimisation et simulation aux systèmes hospitaliers : Application au laboratoire d ’ analyse de biologie médicale et au processus de transfusion sanguine,” 2014.
  19. M. G. Fiestras-Janeiro, I. García-Jurado, A. Meca, and M. A. Mosquera, “Cooperative game theory and inventory management,” Eur. J. Oper. Res., vol. 210, no. 3, pp. 459–466, 2011.
  20. X. Hu, R. Caldentey, and G. Vulcano, “Revenue sharing in airline alliances,” Manage. Sci., 2013.
  21. D. Gillies, “Solutions to general non-zero-sum games,” Contrib. to Theory Games, 1959.
  22. L. Xue, Z. Luo, and A. Lim, “Exact approaches for the pickup and delivery problem with loading cost,” Omega, vol. 59, pp. 131–145, 2016.
  23. M. M. S. Abdulkader, Y. Gajpal, and T. Y. Elmekkawy, “Hybridized ant colony algorithm for the Multi Compartment Vehicle Routing Problem,” Appl. Soft Comput. J., vol. 37, pp. 196–203, 2015.
  24. G. B. Dantzing and J. H. Ramser, “The Truck Dispatching Problem,” Manage. Sci., vol. 6, no. 1, pp. 80–91, 1959.
  25. B. Kallehauge, J. Larsen, and O. B. G. Madsen, “Lagrangian duality applied to the vehicle routing problem with time windows,” Comput. Oper. Res., vol. 33, no. 5, pp. 1464–1487, 2006.
  26. M. M. Solomon, “Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints,” Oper. Res., vol. 35, no. 2, pp. 254–265, 1987.
  27. D. Ta??, N. Dellaert, T. Van Woensel, and T. De Kok, “Vehicle routing problem with stochastic travel times including soft time windows and service costs,” Comput. Oper. Res., vol. 40, no. 1, pp. 214–224, 2013.
  28. M. A. Figliozzi, “An iterative route construction and improvement algorithm for the vehicle routing problem with soft time windows,” Transp. Res. Part C Emerg. Technol., vol. 18, no. 5, pp. 668–679, 2010.
  29. A. Agra, M. Christiansen, R. Figueiredo, L. M. Hvattum, M. Poss, and C. Requejo, “The robust vehicle routing problem with time windows,” Comput. Oper. Res., vol. 40, no. 3, pp. 856–866, 2013.
  30. T. Vidal, T. G. Crainic, M. Gendreau, and C. Prins, “A hybrid genetic algorithm with adaptive diversity management for a large class of vehicle routing problems with time-windows,” Comput. Oper. Res., vol. 40, no. 1, pp. 475–489, 2013.
  31. E. D. Taillard, “A heuristic column generation method for the heterogeneous fleet VRP,” RAIRO - Oper. Res., vol. 33, no. 1, pp. 1–14, 1999.
  32. Y. Dumas, J. Desrosiers, and F. Soumis, “The pickup and delivery problem with time windows,” Eur. J. Oper. Res., vol. 54, no. 1, pp. 7–22, Sep. 1991.
  33. S. Ropke and J.-F. Cordeau, “Branch and Cut and Price for the Pickup and Delivery Problem with Time Windows,” Transp. Sci., vol. 43, no. 3, pp. 267–286, 2009.
  34. R. Baldacci, E. Bartolini, and A. Mingozzi, “An Exact Algorithm for the Pickup and Delivery Problem with Time Windows,” Oper. Res., vol. 59, no. 2, pp. 414–426, Apr. 2011.
  35. M. Cherkesly, G. Desaulniers, S. Irnich, and G. Laporte, “Branch-price-and-cut algorithms for the pickup and delivery problem with time windows and multiple stacks,” Eur. J. Oper. Res., vol. 250, no. 3, pp. 782–793, 2016.
Index Terms

Computer Science
Information Sciences

Keywords

Optimization Game theory Blood supply chain Collaborative logistics VRPPDTW