Abstract
In this chapter we present a survey of location methods based on Nash equilibria for the design of experiments. The solution of the location problem is given in the bi-dimensional case by means of a potential formulation and a Nash game. The most important definitions and proofs are reported. Two main application fields are employed to stress the capability of an ad hoc numerical methodology involved in the solution of the location problem. The first one refers to optimal (constrained) location of sensors collecting cosmic rays for astrophysics experiments. The second one concerns the design of experiment in aerospace engineering related to set of flight tests within the flight envelope of an airplane. An outlook on location-allocation problem in economics is considered for a linear city with congestion in the conclusions.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Anderson, J.D.: Introduction to Flight. McGraw-Hill Series in Aeronautical and Aerospace Engineering, 5th edn. McGraw-Hill, New York (2005)
Arnold, R.J., Epstein, C.S.: Store Separation Flight Testing. NATO AGARDograph 300, Flight Test Technique, vol. 5. Neuilly sur Seine, NATO AGARD (1986)
Başar, T., Olsder, G.J.: Dynamic Noncooperative Game Theory. Classics in Applied Mathematics, vol. 23. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA (1999)
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, pp. 1–18, Springer, Berlin/Heidelberg (2008). doi:10.1007/978-3-540-87921-3_1
Clarich, A., Périaux, J., Poloni, C.: Combining game strategies and evolutionary algorithms for CAD parametrization and multi-point optimization of complex aeronautic systems. In: Proceedings of EUROGEN 2003, Barcelona (2003)
Chinchuluun, A., Pardalos, P.M., Huang, H-X.: Multilevel (hierarchical) optimization: complexity issues, optimality conditions, algorithms. In: Gao, D., Sherali, H. (eds.) Advances in Applied Mathematics and Global Optimization, pp. 197–221. Springer, New York (2009). doi:10.1007/978-0-387-75714-8_6
Conway, J.H., Sloane, N.J.A.: Sphere Packings, Lattices and Groups. Springer, New York (1998). doi:10.1007/978-1-4757-6568-7
D’Amato, E., Daniele, E., Mallozzi, L., Petrone, G.: Equilibrium strategies via GA to Stackelberg games under multiple follower’s best reply. Int. J. Intell. Syst. 27 (2), 74–85 (2012)
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, pp. 267–280. Springer, Berlin (2012). doi:10.1007/978-1-4614-3906-6_14
D’Amato, E., Daniele, E., Mallozzi, L., Petrone, G.: Three level hierarchical decision making model with GA. Engineering Computations: Int. J. Comput.-Aided Eng. Softw. 31 (6), 1116–1128 (2014). doi:10.1108/EC-03-2012-0075
D’Amato, E., Daniele, E., Mallozzi, L.: Experimental design problems and Nash equilibrium solutions. In: Kalyagin, V., Pardalos, P.M., Rassias, T.M. (eds.) Network Models in Economics and Finance. Springer Optimization and Its Applications, vol. 100, pp. 1–12. Springer, Cham (2014). doi:10.1007/978-3-319-09683-4_1
D’Amato, E., Daniele, E., Mallozzi, L.: A genetic algorithm for a sensor device location problem. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds.) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences, pp. 49–57. Springer, Cham (2015). doi:10.1007/978-3-319-11541-2_3
D’Argenio, A., de Nicola, C., De Paolis, P., Di Francesco, G., Mallozzi, L.: Design of a flight test matrix and dynamic relocation of test points. J. Algorithms Optim. 2, 52–56 (2014)
Dean, A.M., Voss, D.: Design and Analysis of Experiments. Springer, New York (1998). doi:10.1007/b97673
Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, New York (2001). ISBN:978-0-471-87339-6
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evolut. Comput. 6 (2), 181–197 (2002). doi:10.1109/4235.996017
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. Academic Press Professional, Inc., San Diego (2004). doi:10.1016/j.jcp.2003.11.022
Drezner, Z.: Facility Location – A Survey of Applications and Methods. Springer, New York (1995). ISBN:978-0-387-94545-3
Eiselt, H.A., Marianov, V.: Foundations of Location Analysis. International Series in Operations Research and Management Science, vol. 115. Springer, New York (2011). doi:10.1007/978-1-4419-7572-0
Gevers, M.: Identification for control – from the early achievements to the revival of experiment design. Eur. J. Control 11 (4), 335–352 (2005). doi:10.3166/ejc.11.335-352
Giunta, A.A., Balabanov, V., Haim, D., Grossman, B., Mason, W.H., Watson, L.T., Haftka, R.T.: Multidisciplinary optimization of a supersonic transport using design of experiments theory and response surface modeling. Technical Report ncstrl.vatech_cs//TR-97-10, Computer Science, Virginia Polytechnic Institute and State University (1997)
Hales, T.C.: The sphere packing problem. J. Comput. Appl. Math. 44 (1), 41–76 (1992). doi:10.1016/0377-0427(92)90052-Y
Mallozzi, L.: Noncooperative facility location games. Oper. Res. Lett. 35 (2), 151–154 (2007). doi:10.1016/j.orl.2006.03.003
Mallozzi, L.: An application of optimization theory to the study of equilibria for games: a survey. Cent. Eur. J. Oper. Res. 21 (3), 523–539 (2012). doi:10.1007/s10100-012-0245-8
Mallozzi, L., D’Amato, E., Daniele, E.: A planar location-allocation problem with waiting time costs. In: Rassias, T.M., Tóth, L. (eds.) Topics in Mathematical and Applications, pp. 541–556. Springer, Cham (2014) doi:10.1007/978-3-319-06554-0_23
Mallozzi, L., D’Amato, E., Daniele, E.: Location methods in experimental design. In: Pardalos, P.M, Rassias, T.M. (eds.) Mathematics Without Boundaries: Surveys of Interdisciplinary Research, pp. 429–446. Springer, New York (2014). doi:10.1007/978-1-4939-1124-0_14
Mallozzi, L., De Paolis, P., Di Francesco, G., D’Argenio, A.: Computational results for flight test points distribution in the flight envelope. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds.) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences, pp. 401–409. Springer, Cham (2015). doi:10.1007/978-3-319-11541-2_26
Migdalas, A., Pardalos, P.M., V’́arbrand, P. (eds.): Multilevel Optimization: Algorithms and Applications. Springer, New York (1998). doi:10.1007/978-1-4613-0307-7
Monderer, D., Shapley, L.S.: Potential games. Games Econ. Behav. 14 (1), 124–143 (1996). doi:10.1006/game.1996.0044
North Atlantic Treaty Organization, Science and Technology Organization: Aircraft/Store Compatibility, Integration and Separation Testing. STO/NATO AGARDograph 300, Flight Test Technique - vol. 29 (2014). ISBN:978-92-837-0214-6
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
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 (5), 417–429 (2001). doi:10.1016/S0168-874X(00)00055-X
Sloane, N.J.A.: The Sphere Packing Problem. 1998 Shannon Lecture, AT&T Shannon Lab, Florham Park, NJ (1998)
Sorokin, A., Pardalos, P.: Dynamics of Information Systems – Algorithmics Approaches. Springer, New York (2013). doi:10.1007/978-1-4614-7582-8
Sutou, A., Dai, Y.: Global optimization approach to unequal sphere packing problems in 3D. J. Optim. Theory Appl. 114 (3), 671–694 (2002). doi:10.1023/A:1016083231326
Telford, J.K.: A Brief Introduction to Design of Experiments. Johns Hopkins University, Applied Physics Laboratory, Technical Digest 27 (3), 224–232 (2007)
Wang, J.F., Périaux, J.: Multi-Point optimization using GAS and Nash/Stackelberg games for high lift multi-airfoil design in aerodynamics. In: Proceedings of the 2001 Congress on Evolutionary Computation CEC2001, pp. 552–559 (2001). doi:10.1109/CEC.2001.934440
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Daniele, E., De Paolis, P., Greco, G.L., d’Argenio, A. (2017). Location Methods and Nash Equilibria for Experimental Design in Astrophysics and Aerospace Engineering. In: Mallozzi, L., D'Amato, E., Pardalos, P. (eds) Spatial Interaction Models . Springer Optimization and Its Applications, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-319-52654-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-52654-6_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-52653-9
Online ISBN: 978-3-319-52654-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)