A linear mathematical programming model for the governmental barter supply chain

Document Type : Research Paper


1 Department of Industrial Engineering, Damavand Branch, Islamic Azad University, damavand, iran

2 engineer of industrial


Exchange of goods with goods or supplies Although the long-standing method is in trade, today, new and emerging networks of national and international networks have found a special place. Aiding economic boom, confronting monetary sanctions, maintaining foreign exchange reserves, maintaining labor force, etc. is one of the benefits of modern markets. Given the widespread presence of these markets, proper management to balance the market, reduce costs, reduce the risk of entry into a network, etc., requires a thorough and math-molded modeling. In this paper, a multipurpose mathematical optimization problem has been designed and implemented with the aim of reducing the costs and liabilities of countries by considering a government-run network of several countries as members of the network to supply the goods needed by each country. The results of solving the proposed model show that the proposed model can provide a suitable model for the production and exchange of goods between the countries forming a public government network.


Main Subjects

  1. O'Sullivan, A., and Sheffrin, S. M., (2007). Economics: Principles in action. Pearson/Prentice Hall.
  2. Zhang, K., and Antonopoulos, N., (2013). “A Novel Bartering Exchange Ring Based Incentive Mechanism For Peer-To-Peer Systems”, Future Generation Computer Systems, Vol. 105, No. 2, PP. 361-369.
  3. Abdulkadiroglu, A., and Sönmez, T., (1999). “House allocation with existing tenants”, Journal of Economic Theory, Vol. 88, No. 2, PP. 233–260.
  4. Syeda, Z., and Peter, B., (2018). “Cloud provider Capacity Augmentation through Automated Resource Bartering”, Future Generation Computer Systems, Vol. 102, No. 1, PP. 203-218.
  5. Roth, A. E., Sönmez, T., and Ünver, M., (2004). “Kidney exchange”, The Quarterly Journal of Economics, Vol. 119, No. 2, PP. 457–488.
  6. Roth, A. E., Sönmez, T., and Ünver, M. (2005). “A kidney exchange clearinghouse in new England”, American Economic Review, PP. 376–380.
  7. Sönmez, T., and Switzer, T. B., (2013). “Matching with (branch-of-choice) Contracts at the United States Military Academy”, Econometric, Vol. 81, No. 2, PP. 451–488.
  8. Fang, W., Tang, P., and Zuo, S., (2016). “Digital good exchange”, In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016, PP. 264–270.
  9. Luo, S., and Tang, P., (2015). “Mechanism Design and Implementation for Lung Exchange”, In IJCAI.
  10.  Li, J.  et al., (2014). “Egalitarian Pairwise Kidney Exchange: Fast Algorithms Vialinear Programming and Parametric Flow”, In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-Agent Systems, PP. 445–452.
  11.  Abraham, D. J., Blum, A., and Sandholm, T., (2007). “Clearing Algorithms for Barter Exchange Markets: Enabling Nationwide Kidney Exchanges”, In Proceedings of the 8th ACM Conference on Electronic Commerce, PP. 295–304.
  12.  Sobhanallahi, M. A. and Kohgard, A., (2016). “Productivity Method for Economic Growth without Liquidity Growth”, Journal of Research in Economic Modeling, Vol. 6, No. 24, PP. 201-225.
  13.  Kim, B. Y. and Pirttilä, J., (2004). “Money, barter, and inflation in Russia”, Journal of Comparative Economics, Vol. 32, No. 2, PP. 297-314.
  14.  Maria, J., and Elena, R., (2018). “Aligning Supply Chain Design for Boosting Resilience”, Business Horizons,Vol. 29, No. 2, PP. 85-93.
  15.  Sreedevi, R., and Saranga, H., (2017). “Uncertainty and Supply Chain Risk: The Moderating Role of Supply Chain Flexibility In Risk Mitigation”, International Journal of Production Economics, Vol. 193, , PP. 332-342
  16.  Banerjee, A.V., and Maskin, E. S., (1996). “A Walrasian Theory of Money and Barter”, The Quarterly Journal of Economics, Vol. 111, No. 4, PP. 955-1005.
  17.  Cellarius, B. A., (2000). “You Can Buy Almost Anything with Potatoes: An Examination of Barter During Economic Crisis in Bulgaria”, Ethnology, Vol. 39, No. 1, PP. 73-92.
  18.  Chen, S., and Kao, Y. C., (2010). “Money, barter, and consumption interdependence”, Economics Letters, Vol. 106, No. 2, PP. 119-121.
  19.  Núñez, M., Rodríguez, I., and Rubio, F., (2005). “Formal specification of multi-agent e-barter systems”, Science of Computer Programming, Vol. 57, No. 2, PP. 187-216.
  20.  Sudzina, F., (2012). “Motives for Barter in Developing, Transition, And Developed Economies”, 1st International Conference on Economics, Political and Law Science, Zlin, Czech Republic, PP. 125-129.
  21.  Anderson, R.  et al., (2014). “A Dynamic Model of Barter Exchange”, In Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, PP. 1925-1933
  22. 22.               Taleizadeh, A., and Dariyan, M., (2018). “Developing a Model of Economic Production in Integrated and Non-Integrated Three-Level Supply Chains with Consideration of Optimal Inventory Control Policy”, Industrial Engineering Journal, Vol. 52, No. 1, PP. 125-137. (In Persian)
  23.  Akbari Jokar, M. R., Abochenari, M., and Akefi, H., (2016). “Designinig of Chain Network to Provide Complete Packet Ring Under the Conditions of Demand Uncertainty and Return of Products”, Industrial Engineering Journal, Vol. 50, No. 3, PP. 355-369. (In Persian)
  24.  A linear mathematical programming model for the governmental barter supply chain
  25.  Meghdad Haji Mohammad Ali Jahromim, Abbas Kashaniyan
  26.  Meghdad Haji Mohammad Ali Jahromim , Assistant Professor of Industrial engineering Department, Damavand Branch, Islamic Azad University, Damavand, Iran
  27.  Abbas Kashaniyan, Graduated of Master of Science, Industrial engineering Department, Damavand Branch, Islamic Azad University, Damavand, Iran