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A game theoretical approach to emergency logistics planning in natural disasters

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Abstract

Nowadays, logistics is one of the most important tools in disaster relief operations. The logistic planning is essential and a key component in covering the initial needs in the immediate aftermath of any disaster. Planning is both necessary and practical, as it is generally possible to predict the types of disasters that should affect a given location and the needs that such disasters will be likely to cause. Transport planning, reception and distribution of emergency supplies, type and quantity of the resources, the way of procurement and storage of the supplies, the tools of the tracking and means transportation to the stricken area, the specialization of teams participating in the operation and plan of cooperation between these teams, are some vital life-saving coordination roles after natural disasters are connected directly to logistic planning. Turkey is located in one of the most active earthquake and volcanic regions which causes to many major earthquake-prone, in the world with a majority of the population living in these earthquake-prone areas. Earthquakes are one of the major disasters that require emergency logistic planning strategies due to their devastating effects, the large-scale natural disasters could cause major problem on commodities such as food, medicine etc. In this paper, a game theoretical model for emergency logistic planning is developed. To do this a cooperative game model is constructed from a flow problem which occurred after an earthquake in Istanbul. Several solution concepts for maximizing the transferred commodity are given. The paper ends with a conclusion and outlook to future studies.

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References

  • Aparicio, J., Llorca, N., Sanchez-Soriano, J., Sancho, J., & Valero, S. (2010). Cooperative logistics games. SCIYO. COM, 129.

  • Baharmand, H., Comes, T., & Lauras, M. (2019). Defining and measuring the network flexibility of humanitarian supply chains: Insights from the 2015 Nepal earthquake. Annals of Operations Research, 283(1), 961–1000

    Google Scholar 

  • Baidya, A., & Bera, U. K. (2019). New model for addressing supply chain and transport safety for disaster relief operations. Annals of Operations Research, 283(1–2), 33–69

    Google Scholar 

  • Barbarosoğlu, G., Özdamar, L., & Cevik, A. (2002). An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research, 140(1), 118–133

    Google Scholar 

  • Bertsimas, D., & Thiele, A. (2004). A robust optimization approach to supply chain management. In International conference on integer programming and combinatorial optimization (pp. 86–100). Springer Berlin.

  • Branzei, R., Dimitrov, D., & Tijs, S. (2008). Models in cooperative game theory. (Vol. 556)New York: Springer.

    Google Scholar 

  • Cachon, G. P., & Netessine, S. (2004). Game theory in supply chain analysis. In Handbook of quantitative supply chain analysis (pp. 13–65). Springer US.

  • Caunhye, A. M., Nie, X., & Pokharel, S. (2012). Optimization models in emergency logistics: A literature review. Socio-Economic Planning Sciences, 46(1), 4–13

    Google Scholar 

  • Çetin, H. C. (2013). Disaster crises management in Turkey: 1999 Marmara earthquake case. Journal of Human Sciences, 10(2), 628–636

    Google Scholar 

  • Chang, M. S., Tseng, Y. L., & Chen, J. W. (2007). A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E: Logistics and Transportation Review, 43(6), 737–754

    Google Scholar 

  • Christopher, M. (2016). Logistics and supply chain management. Pearson UK.

  • Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply chain management: More than a new name for logistics. The International Journal of Logistics Management, 8(1), 1–14

    Google Scholar 

  • Curiel, I. (2013). Cooperative Game Theory and applications: cooperative games arising from combinatorial optimization problems. (Vol. 16)New York: Springer.

    Google Scholar 

  • Deng, X., Fang, Q., & Sun, X. (2009). Finding nucleolus of flow game. Journal of Combinatorial Optimization, 18(1), 64–86

    Google Scholar 

  • Driessen, T., & Tijs, S. H. (1983). The t-value, the nucleolus and the core for a subclass of games (No. 73fdfe73-c88c-4a9f-8ee7-cd3d26003ea7). Tilburg University, School of Economics and Management.

  • Dubey, R., Gunasekaran, A., & Papadopoulos, T. (2019). Disaster relief operations: Past, present and future. Annals of Operations Research, 283(1–2), 1–8

    Google Scholar 

  • Esmaeili, M., Aryanezhad, M.-B., & Zeephongsekul, P. (2009). A game theory approach in seller–buyer supply chain. European Journal of Operational Research, 195(2), 442–448

    Google Scholar 

  • Ferguson, T. S. (2000). Game theory, optimal stopping, probability and statistics: Papers in honor of Thomas S. Ferguson. Institute of Mathematical Statistics.

  • Fiedrich, F., Gehbauer, F., & Rickers, U. (2000). Optimized resource allocation for emergency response after earthquake disasters. Safety Science, 35(1), 41–57

    Google Scholar 

  • Ganeshan, R., & Harrison, T. P. (1995). An introduction to supply chain management. Department of Management Sciences and Information Systems, 303.

  • Goli, A., Tirkolaee, E. B., Malmir, B., Bian, G. B., & Sangaiah, A. K. (2019). A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand. Computing, 101(6), 499–529

    Google Scholar 

  • Gu, Q., Gao, T., & Shi, L. (2005). Price decision analysis for reverse supply chain based on game theory. Systems Engineering-Theory and Practice, 20(3), 20–25

    Google Scholar 

  • Gunn, S. W. A. (2003). The language of disasters: A brief terminology of disaster management and humanitarian action. In Basics of international humanitarian missions (pp. 37–40).

  • Hamiel, Y., & Fialko, Y. (2007). Structure and mechanical properties of faults in the North Anatolian Fault system from InSAR observations of coseismic deformation due to the 1999 Izmit (Turkey) earthquake. Journal of Geophysical Research: Solid Earth, 112(B7), 2008

    Google Scholar 

  • Hennet, J.-C., & Arda, Y. (2008). Supply chain coordination: A game-theory approach. Engineering Applications of Artificial Intelligence, 21(3), 399–405

    Google Scholar 

  • Kalai, E., & Zemel, E. (1982). Totally balanced games and games of flow. Mathematics of Operations Research, 7(3), 476–478

    Google Scholar 

  • Ketchen, D. J., & Hult, G. T. M. (2007). Bridging organization theory and supply chain management: The case of best value supply chains. Journal of Operations Management, 25(2), 573–580

    Google Scholar 

  • Kim, S., Ramkumar, M., & Subramanian, N. (2019). Logistics service provider selection for disaster preparation: A socio-technical systems perspective. Annals of Operations Research, 283(1–2), 1259–1282

    Google Scholar 

  • Kolukirik, S., & Tuna, M. (2009). Türk Medyasinda Deprem Algısı: Marmara Depremi Örneği. Elektronik Sosyal Bilimler Dergisi, 28(28), 286–298

    Google Scholar 

  • Nagarajan, M., & Sošić, G. (2008). Game-theoretic analysis of cooperation among supply chain agents: Review and extensions. European Journal of Operational Research, 187(3), 719–745

    Google Scholar 

  • Özdamar, L., Ekinci, E., & Küçükyazici, B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, 129(1–4), 217–245

    Google Scholar 

  • Palancı, O., Gök, S. A., Olgun, M. O., & Weber, G. W. (2016). Transportation interval situations and related games. Or Spectrum, 38(1), 119–136

    Google Scholar 

  • Ray, J. (1987). A multi-period linear programming model for optimally scheduling the distribution of food-aid in West Africa.

  • Reyes, P. M. (2005). Logistics networks: A game theory application for solving the transshipment problem. Applied Mathematics and Computation, 168(2), 1419–1431

    Google Scholar 

  • Sabouhi, F., Bozorgi-Amiri, A., Moshref-Javadi, M., & Heydari, M. (2019). An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: a case study. Annals of Operations Research, 283(1–2), 643–677

    Google Scholar 

  • Salehi, F., Mahootchi, M., & Husseini, S. M. M. (2019). Developing a robust stochastic model for designing a blood supply chain network in a crisis: A possible earthquake in Tehran. Annals of Operations Research, 283(1), 679–703

    Google Scholar 

  • Sánchez-Soriano, J., Lopez, M. A., & Garcia-Jurado, I. (2001). On the core of transportation games. Mathematical Social Sciences, 41(2), 215–225

    Google Scholar 

  • Schmeidler, D. (1969). The nucleolus of a characteristic function game. SIAM Journal on Applied Mathematics, 17(6), 1163–1170

    Google Scholar 

  • Shapley, L. S. (1953). Stochastic games. Proceedings of the National Academy of Sciences, 39(10), 1095–1100

    Google Scholar 

  • Sheu, J. B. (2007). Challenges of emergency logistics management. Transportation Research Part e: Logistics and Transportation Review, 43(6), 655–659

    Google Scholar 

  • Taş, N. (2003). Reducing probable earthquake damages in urban settlements. Uludağ Üniversitesi Mühendislik Ve Mimarlık Fakültesi Dergisi, 8(1), 225–231

    Google Scholar 

  • Thomas, D. J., & Griffin, P. M. (1996). Coordinated supply chain management. European Journal of Operational Research, 94(1), 1–15

    Google Scholar 

  • Thun, J.-H. (2005). The potential of Cooperative Game Theory for supply chain management. In Research methodologies in supply chain management (pp. 477–491): Springer.

  • Tijs, S. (1981). Bounds for the core of a game and the t-value. Tilburg University, School of Economics and Management.

  • Tijs, S. H. (2003). Introduction to game theory. SIAM Hindustan Book Agency.

    Google Scholar 

  • Tirkolaee, E. B., Goli, A., & Weber, G. W. (2020). Fuzzy mathematical programming and self-adaptive artificial fish swarm algorithm for just-in-time energy-aware flow shop scheduling problem with outsourcing option. IEEE Transactions on Fuzzy Systems, 28(11), 2772–2783

    Google Scholar 

  • Van Wassenhove, L. N. (2006). Humanitarian aid logistics: supply chain management in high gear†. Journal of the Operational Research Society, 57(5), 475–489

    Google Scholar 

  • Yahyaei, M., & Bozorgi-Amiri, A. (2019). Robust reliable humanitarian relief network design: An integration of shelter and supply facility location. Annals of Operations Research, 283(1), 897–916

    Google Scholar 

  • Yerlikaya, Ö. F., Askan, A., & Weber, G. W. (2014). An alternative approach to the ground motion prediction problem by a non-parametric adaptive regression method. Engineering Optimization, 46(12), 1651–1668

    Google Scholar 

  • Yerlikaya, Ö. F., Askan, A., & Weber, G.-W. (2017). A hybrid computational method based on convex optimization for outlier problems: Application to earthquake ground motion prediction. Informatica, 27(4), 893–910

    Google Scholar 

  • Yuan, Y., & Wang, D. (2009). Path selection model and algorithm for emergency logistics management. Computers and Industrial Engineering, 56(3), 1081–1094

    Google Scholar 

  • Yucemen, M. S. (2005). Probabilistic assessment of earthquake insurance rates for Turkey. Natural Hazards, 35(2), 291–313

    Google Scholar 

  • Zhang, J., Wang, Z., & Ren, F. (2019). Optimization of humanitarian relief supply chain reliability: A case study of the Ya’an earthquake. Annals of Operations Research, 283(1), 1551–1572

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Engineering, Isparta University of Applied Sciences, Isparta, Turkey

    Serap Ergün

  2. Department of Civil Engineering, Isparta University of Applied Sciences, Isparta, Turkey

    Pınar Usta

  3. Department of Mathematics, Suleyman Demirel University, Isparta, Turkey

    Sırma Zeynep Alparslan Gök

  4. Poznan University of Technology, Poznań, Poland

    Gerhard Wilhelm Weber

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  1. Serap Ergün
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  2. Pınar Usta
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  3. Sırma Zeynep Alparslan Gök
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  4. Gerhard Wilhelm Weber
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Correspondence to Serap Ergün.

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Ergün, S., Usta, P., Alparslan Gök, S.Z. et al. A game theoretical approach to emergency logistics planning in natural disasters. Ann Oper Res 324, 855–868 (2023). https://doi.org/10.1007/s10479-021-04099-9

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