D
Linear and Nonlinear Programming
  1. A Combinatorial Theory of Linear Programming, Mathematical Paperes (Matematikai Lapok) 22(1971) 7-24 (in Hungarian).
  2. Extension of the Method of Feasible Directions to the Case of Quasi-Concave Constraining Functions. Publications of the Computing Centre of the H.A.S. 9(1972) 3-16 (in Hungarian).
  3. Eine Erweiterung der sogenannten Methode der "zulassigen Richtungen" der nichtlinearen Optimierung auf den Fall quasikonkaver Restriktions-funktionen. Mathematische Operationsforchung und Statistik 5(1974) 281-293.
  4. On the Development of Optimization Theory. Applied Mathematical Papers (Alkalmazott Matematikai Lapok) 4(1978) 165-191 (in Hungarian).
  5. Probabilistic Bounds and Algorithms for the Maximum Satisfiability Problem. Annals of Operations Research 21 (1989) 109-126. With E. Boros.
  6. Dual Method for a One-Stage Stochastic Programming Problem with Random RHS, Obeying a Discrete Probability Distribution. Zeitschrift für Operations Research 34(1990) 441-461.
  7. Solution of and a Bounding in Linearly Constrained Optimization Problem with Convex, Polyhedral Objective Function. Mathematical Programming, 70 (1995) 1-16. With W. Li.
  8. A Brief Introduction to Linear Programming. Mathematical Scientist, 21(1996) 85-111.
  9. One-sided approximation of multivariate discrete functions by polynomials. Applied Math. Papers (Alkalmazott Matematikai Lapok) 20 (2000) 195-215. With G. Mádi-Nagy (in Hungarian).
  10. On a Dual Method for a Specially Structured Linear Programming Problem with Application to Stochastic Programming. Optimization Methods and Software 17 (2002) 445-492. With C. Fábián and O. Ruff-Fiedler.
  11. Linear Inequalities, Duality Theorems and their Financial Applications. In: Proceedings of the International Conference in Memoriam Gyula Farkas (held in Cluj, August 2005, Z.Kása, G. Kassay, J. Kolumbán, editors). Cluj University Press, 2006, 8-21.
  12. Monge Property and Bounding Multivariate Probability Distribution Functions with Given Marginals and Covariances. SIAM J. on Optimization. 18 (2007) 138-155. With X. Hou.
  13. Convex approximations in stochastic programming by semidefinite programming. Annals of Operations Research, to appear. With I. Deák, I. Pólik, T. Telaky.