Professoren
Prof. Dr. rer. nat. János Mayer

Prof. Dr. rer. nat. János Mayer

Gyula Farkas Prize 1979 Applied Mathematics. János Bolyai Mathematical Society, Hungary.Books

[2005a] P. Kall and J. Mayer. Stochastic Linear Programming. Models, Theory and Computation.
International Series in Operations Research 80, Springer Verlag, 2005.

[1998a] J. Mayer. Stochastic Linear Programming Algorithms: A Comparison Based on a Model
Management System. Gordon and Breach Science Publishers, 1998.Refereed papers

[2006a] A. Künzi-Bay and J. Mayer . Computational aspects of minimizing conditional value-at-risk.
Computational Management Science, 3:3-27, 2006.

[2006b] P. Kall and J. Mayer. Some insights into the solution algorithms for SLP problems, Annals of
Operations Research, 142:147-164, 2006.

[2005b] T. Hens, J. Mayer, and B. Pilgrim. Existence of sunspot equilibria and uniqueness of spot market
equilibria: The case of intrinsically complete markets, In A. Citanna, J. Donaldson, H.
Polemarchakis, P. Sciconolfi, and S. Spear, editors, Essays in Dynamic General Equilibrium, Festschrift David Cass, Studies in Economic Theory 20, pp. 75–106. Springer Verlag, 2005.

[2004a] P. Kall and J. Mayer. Modeling support for multistage recourse problems, In K. Marti, Y. Ermoliev, and G. Pflug, editors, Dynamic stochastic optimization, Lecture Notes in Economics and Math. Systems 532, pp. 21–41. Springer Verlag, 2004.

[2000b] P. Kall and J. Mayer. On the role of bounds in stochastic linear programming, Optimization, 47:287–301, 2000.

[1998b] P. Kall and J. Mayer. On solving stochastic linear programming problems, In K. Marti and P. Kall, editors, Stochastic Programming Methods and Technical Applications, Lecture Notes in Economics and Math. Systems 458, pp. 329–344. Springer Verlag, 1998.

[1998c] P. Kall and J. Mayer. On testing SLP codes with SLP–IOR. In F. Giannessi, T. Rapcsák, and S. Komlósi, editors, New trends in mathematical programming, pp. 115–135. Kluwer Academic Publishers, 1998.

[1996] P. Kall and J. Mayer. SLP–IOR: An interactive model management system for stochastic linear programs, Mathematical Programming, 75:221–240, 1996.

[1995a] P. Kall and J. Mayer. Computer support for modeling in stochastic linear programming. In K. Marti and P. Kall, editors, Stochastic Programming: Numerical Techniques and Engineering Applications, Lecture Notes in Economics and Math. Systems 423, pp. 54–70. Springer Verlag, 1995.

[1994a] T. Illés, J. Mayer, and T. Terlaky. Pseudoconvex optimization for a special problem of paint industry. European Journal on Operational Research, 79:537–548, 1994.

[1993a] J. Mayer. Probabilistic constrained optimization — a brief summary on theory and algorithms.
Revista Investigacion Operacional, 14:162–174, 1993.

[1993b] P. Kall and J. Mayer. SLP-IOR: On the design of a workbench for testing SLP codes. Revista Investigacion Operacional, 14:148–161, 1993.

[1992a] J. Mayer. Computational techniques for probabilistic constrained optimization problems. In K.
Marti, editor, Stochastic Optimization: Numerical Methods and Technical Applications, Lecture Notes in Economics and Math. Systems 379, pp. 141–164. Springer Verlag, 1992.

[1992b] M. Biro, J. Mayer, T. Rapcsák, and M. Vermes. On expert systems in mathematical programming. Alkalmazott Matematikai Lapok, 16:217–278, 1992. (in Hungarian).

[1992c] P. Kall and J. Mayer. SLP-IOR: A model management system for stochastic linear programming,
system design. In A.J.M. Beulens and H.-J. Sebastian, editors, Optimization-Based Computer-Aided Modelling and Design, Lecture Notes in Control and Information Sciences 174, pp. 139–157. Springer Verlag, 1992.

[1992d] P. Kall and J. Mayer. „A model management system for stochastic linear programming. In P. Kall,
editor, System Modelling and Optimization, Lecture Notes in Control and Information Sciences 180, pp. 580–587. Springer Verlag, 1992.

[1992e] E. Klafszky, J. Mayer, and T. Terlaky. A geometric programming approach to the channel capacity problem. Engineering Optimization, 19:115–130, 1992.

[1991] M. Biro, J. Mayer, T. Rapcsák, and M. Vermes. On building mathematical programming expert systems. In Proceedings of the Second Conference on Artificial Intelligence, Vol. 1, pp. 155–163. John von Neumann Society for Computer Sciences, Hungary, 1991.

[1990a] K. Balla, S. Doleschall, and J. Mayer. On the computation of multiphase equilibria. Engineering
Optimization, 15:295–310, 1990.

[1990b] E. Klafszky, J. Mayer, and T. Terlaky. A new convergent algorithm for the continuous modular
design problem. Arabian Journal of Science and Engineering, 15:687–694, 1990.

[1989a] E. Klafszky, J. Mayer, and T. Terlaky. On mathematical models of the mixing problem.
Alkalmazott Matematikai Lapok, 14:99–117, 1989. (in Hungarian).

[1989b] E. Klafszky, J. Mayer, and T. Terlaky. Linearly constrained estimation by mathematical programming. European Journal on Operational Research, 42:254–267, 1989.

[1989c] E. Klafszky, J. Mayer, and T. Terlaky. A new algorithm for the continuous modular design problem. In Proceedings of the SIGAL Workshop on Algorithms. Association of Information Science of Japan, Tokyo, 1989.

[1985a] I. Deák, J. Hoffer, J. Mayer, Németh A., B. Potecz, and A. Prékopa. Recent advances concerning the problem of optimal daily scheduling of electricity production in Hungary. In J. Gertler and L. Keviczky, editors, A Bridge Between Control Science and Technology, Vol. 4., pp. 2157–2162. Pergamon Press, Oxford, 1985.

[1985b] J. Mayer and A. Prékopa. On the load flow problem of electric power systems. In Hj. Wacker, editor, Applied Optimization Techniques in Energy Problems, pp. 321–340. Teubner Verlag, 1985.

[1983] I. Deák, J. Hoffer, J. Mayer, Németh A., B. Potecz, and A. Prékopa. A large scale, mixed variable mathematical programming model for the short-range optimal schedule of electric power systems with thermal power plants taking network constraints into account. Alkalmazott Matematikai
Lapok, 9:221–337, 1983. (in Hungarian).

[1982] I. Deák, J. Hoffer, J. Mayer, Németh A., B. Potecz, and A. Prékopa. Optimal daily scheduling of the electricity production in Hungary. In G. Feichtinger and P. Kall, editors, Operations Research in Progress, pp. 103–114. D. Reidel Publ. Co., 1982.

[1981] I. Deák, J. Hoffer, J. Mayer, Németh A., B. Potecz, and A. Prékopa. Optimal daily scheduling of the electricity production in Hungary. In G. B. Dantzig, M. A. H. Dempster, and M. Kallio, editors, Large Scale Linear Programming, pp. 923–960. IIASA, Laxenburg, Austria, 1981.

[1979a] P. Kas and J. Mayer. On a solution method for the nonlinear network flow problem. Alkalmazott Matematikai Lapok, 5:157–164, 1979. in Hungarian.

[1979b] J. Mayer. A nonlinear programming method for the solution of a stochastic programming model of A. Prekopa. In A. Prékopa, editor, Survey of Mathematical Programming, Vol. 2., pp. 129–139. North-Holland Publ. Co., 1979.

[1976a] J. Mayer. On the STABIL stochastic programming model. Alkalmazott Matematikai Lapok, 2:171–187, 1976. in Hungarian.

[1974] J. Mayer. Computational experiences with the reduced gradient method. In A. Prékopa, editor, Progress in Operations Research, pp. 613–624. North-Holland Publ. Co., 1974.


Invited contributions in books

[2006c] J. Mayer. On the numerical solution of stochastic optimization problems. In F. Ceragioli, A. Dontchev, H. Futura, K. Marti, and L. Pandolfi, editors, System Modeling and Optimization, pp. 193-206. Springer Verlag, 2006.

[2005e] P. Kall and J. Mayer. Building and solving stochastic linear programming models with SLP-IOR.
In S.W. Wallace and W.T. Ziemba, editors, Applications of Stochastic Programming, MPSSIAM Book Series on Optimization 5, pp. 79-93, 2005.

[2000a] J. Mayer. On the numerical solution of jointly chance constrained problems. In S. Uryasev, editor,
Probabilistic constrained optimization: Methodology and applications, pp. 220–233. Kluwer Academic Publishers, 2000.


Other publications

[2006d] E. De Giorgi, T. Hens, and J. Mayer. A behavioral foundation of reward-risk portfolio selection and the asset allocation puzzle. NCCR FINRISK Working Paper 286. May 2006.

[2006e] E. De Giorgi, T. Hens, and J. Mayer. Computational aspects of prospect theory with asset pricing applications. NCCR FINRISK Working Paper 274. January 2006.

[2005c] A. Künzi-Bay and J. Mayer. Computational aspects of minimizing conditional value-at-risk. NCCR FINRISK Working Paper 211. March 2005.

[2004d] T. Hens, J. Mayer, and B. Pilgrim. Existence of sunspot equilibria and uniqueness of spot market
equilibria: The case of intrinsically complete markets. IEW Working Paper 188, University of Zurich, May 2004.

[2002a] P. Kall and J. Mayer. SLP-IOR V2.1.2. User’s Guide. Institute for Operations Research, University of Zurich, 2002. 217 pages.

[2001a] P. Kall, J. Mayer, and S. Muster. Stochastic variants of the ALM/CFM model. IOR University of Zurich, 2001. Discussion paper, 44 pages.

[2001b] J. Mayer. The distribution of aggregate claims. IOR University of Zurich, 2001. Discussion paper, 19 pages.

[1995b] J. Mayer. Stochastic linear programming algorithms: A comparison based on a model management system, 1995. Wirtschaftswissenschaftliche Fakultät, Universität Zürich, Habilitationsschrift.

[1994b] P. Kall and J. Mayer. SLP-IOR: A model management system for stochastic linear programming.
In G. Hellwig, P. Kall, and P. Abel, editors, Statistical Methods for Decision Processes, pp. 54–63. Daimler Benz AG, Stuttgart-Möhringen, 1994.

[1988a] J. Mayer. Probabilistic constrained programming: A reduced gradient algorithm implemented on PC. Working Paper WP-88-39, IIASA, 1988.

[1988b] P. Csáki, J. Mayer, and E. Szelke. A taxonomy of decision support methods. Technical report, OMFB, State Committee for Technological Development, Hungary, 1988. in Hungarian.

[1986] J. Mayer. Mathematical programming problems based on quadratic functions and some of their
applications, 1986. Hungarian Academy of Sciences, Candidate Thesis in Hungarian.

[1984] I. Deák, J. Hoffer, J. Mayer, Németh A., B. Potecz, and A. Prékopa. Short–range optimal scheduling of an electric energy system of thermal power plants taking network constraints into account. MTA SzTAKI Tanulmányok 155, Computer and Automation Institute, Hungarian Academy of Sciences, 1984. 207 pp.

[1983] I. Deák, J. Hoffer, J. Mayer, Németh A., B. Potecz, and A. Prékopa. Optimal daily scheduling of the electricity production in Hungary. In A. Prékopa and G. Kéri, editors, Operations Research Software Descriptions, pp. 43–68. Computer and Automation Institute, Hungarian Academy of
Sciences, 1983. MTA SzTAKI Tanulmányok 152.

[1976b] J. Mayer. A new algorithm for the solution of the STABIL stochastic programming model, 1976. Eötvös Loránd University, Budapest, doctoral Thesis in Hungarian.

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