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Experimental Design Problems and Nash Equilibrium Solutions

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Network Models in Economics and Finance

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 100))

Abstract

In this paper we present a non-cooperative game theoretical model for the well-known problem of experimental design. Nash equilibrium solutions of a suitable game will be the optimal values of the design variables, given by the coordinates of points in a region in the spirit of the facility location model. Because of the dependency of the objective functions on the distance from the domain’s boundary, this problem has a strong analogy with the classical sphere packing problem. Theoretical and computational results are presented for this location problem by virtue of a genetic algorithm procedure for both two- and three-dimensional test cases.

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References

  1. Başar, T., Olsder, G.J.: Dynamic noncooperative game theory. In: Classics in Applied Mathematics, vol. 23. Society for Industrial and Applied Mathematics (SIAM), Philadelphia (1999). Reprint of the second (1995) edition

    Google Scholar 

  2. Benabbou, A., Borouchaki, H., Laug, P., Lu, J.: Sphere packing and applications to granular structure modeling. In: Garimella, R.V. (eds.) Proceedings of the 17th International Meshing Roundtable, 12–15 October. Springer, Berlin (2008)

    Google Scholar 

  3. Conway, J.H., Sloane, N.J.A.: Sphere Packings, Lattices and Groups. Springer, New York (1998)

    Google Scholar 

  4. D’Amato, E., Daniele, E., Mallozzi, L., Petrone G.: Equilibrium strategies via GA to Stackelberg games under multiple follower best reply. Int. J. Intell. Syst. 27, 74–85 (2012)

    Article  Google Scholar 

  5. D’Amato, E., Daniele, E., Mallozzi, L., Petrone, G., Tancredi, S.: A hierarchical multi-modal hybrid Stackelberg-nash GA for a leader with multiple followers game. In: Sorokin, A., Murphey, R., Thai, M.T., Pardalos, P.M. (eds.) Dynamics of Information Systems: Mathematical Foundations. Springer Proceedings in Mathematics & Statistics, vol. 20, pp. 267–280. Springer, New York (2012)

    Google Scholar 

  6. Dean, A., Voss, D.: Design and Analysis of Experiments. Springer Texts in Statistics. Springer, Dordrecht (1998)

    Google Scholar 

  7. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 81–197 (2002)

    Article  Google Scholar 

  8. Donev, A., Torquato, S., Stillinger, F.H., Connelly, R.: A linear programming algorithm to test for jamming in hard-sphere packings. J. Comput. Phys. 197(1), 139–166 (2004). doi:10.1016/j.jcp.2003.11.022

    Article  MathSciNet  MATH  Google Scholar 

  9. Fudenberg, D., Tirole, J.: Game Theory. The MIT Press, Cambridge (1993)

    Google Scholar 

  10. Hales, T.C.: The sphere packing problem. J. Comput. Appl. Math. 42, 41–76 (1992)

    Article  MathSciNet  Google Scholar 

  11. Mallozzi, L.: Noncooperative facility location games. Oper. Res. Lett. 35, 151–154 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  12. Mallozzi, L., D’Amato, E., Daniele E.: A game theoretical model for experiments design optimization. In T.M. Rassias, C.A. Floudas, S. Butenko (Eds.) Optimization in Science and Engineering, In Honor of the 60th Birthday of Panos M. Pardalos, Springer (2014)

    Google Scholar 

  13. Migdalas, A., Pardalos, P.M., Varbrand, P. (eds.) Multilevel Optimization: Algorithms and Applications. Kluwer Academic, Dordrecht (1997)

    Google Scholar 

  14. Nurmela, K.J.: Stochastic optimization methods in sphere packing and covering problems in discrete geometry and coding theory. Ph.D. thesis, Helsinki University of Technology, printed by Picaset Oy (1997)

    Google Scholar 

  15. Periaux, J., Chen, H.Q., Mantel, B., Sefrioui, M., Sui, H.T.: Combining game theory and genetic algorithms with application to DDM-nozzle optimization problems. Finite Elem. Anal. Des. 37, 417–429 (2001)

    Article  MATH  Google Scholar 

  16. Sloane, N.J.A.: The Sphere Packing Problem. 1998 Shannon Lecture. AT&T Shannon Lab, Florham Park, NJ (1998)

    Google Scholar 

  17. Sorokin, A., Pardalos, P. (eds.): Dynamics of Information Systems: Algorithmics Approaches, Sorokin, A., Pardalos, P. (eds.): Springer Proceedings in Mathematics & Statistics, vol. 51 (2013)

    Google Scholar 

  18. Sutou, A., Dai, Y.: Global optimization approach to unequal sphere packing problems in 3D. J. Optim. Theory Appl. 114(3), 671–694 (2002)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Lina Mallozzi .

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D’Amato, E., Daniele, E., Mallozzi, L. (2014). Experimental Design Problems and Nash Equilibrium Solutions. In: Kalyagin, V., Pardalos, P., Rassias, T. (eds) Network Models in Economics and Finance. Springer Optimization and Its Applications, vol 100. Springer, Cham. https://doi.org/10.1007/978-3-319-09683-4_1

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