Stochastic Programming


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  3. Bereanu, B. : On Stochastic Linear Programming : The Laplace Transform of the Distribution of the Optimum and Applications. Journal of Mathematical Analysis and Applications 15 (1966) 280-294.
  4. Bilbro, G.L. : Fast Stochastic Global Optimization, IEEE Trans. Systems, Man and Cybernetics 24 (1994) 684-689.
  5. Birge, J.R. and Qi, L. : Subdifferential Convergence in Stochastic Programs, SIAM J. Optimization 5 (1995) 436-453.
  6. Carraway, R.L., Schmidt, R.L. and Weatherford, L.R. : An Algorithm for Maximizing Target Achievement in the Stochastic Knapsack Problem with Normal Returns, Naval Research Logistics 40 (1993) 161-173.
  7. Charnes, A. and Cooper, W.W. : Chance-Constrained Programming, Management Science 6 (1959) 73-79.
  8. Charnes, A. and Cooper, W.W. : Chance Constrainted Programs with Normal Deviates and Linear Decision Rules, Naval Research Logistics Quarterly 7 (1960) 533-544.
  9. Charnes, A. and Cooper, W.W. : Chance Constraints and Normal Deviates, J. American Statistical Association 57 (1962) 134-148.
  10. Charnes, A., Cooper, W.W. and Thompson, G.L. : Critical Path Analysis via Chance Constrained and Stochastic Programming, Operations Research 12 (1964) 460-470.
  11. Charnes, A., Cooper, W.W. and Thompson, G.L. : Constrained Generalized Medians and Hypermedians as Deterministic Equivalents for Two-Stage Linear Programs under Uncertainty, Management Science 12 (1965) 83-112.
  12. Charnes, A. and Kirby, M.J.L. : Some Special P-Models in Chance-Constrained Programming, Management Science 14 (1967) 183-195.
  13. Charnes, A. and Cooper, W.W. : Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints. Operations Research 11 (1963) 18-39.
  14. Charnes, A., Kirby, M.J.L. and Raike, W.M. : An Acceptance Region Theory for Chance-Constrained Programming. Journal of Mathematical Analysis and Applications 32 (1970) 38-61.
  15. Contini, B. : A Stochastic Approach to Global Programming, Operations Research 16 (1968) 576-586.
  16. Culioli, J.-C. and Cohen, G. : Decomposition/Coordination Algorithms in Stochastic Optimization. SIAM J. Control and Optimization 28 (1990) 1372-1403.
  17. Dantzig, G.B. : Linear Programming under Uncertainty. Management Scienve 1 (1955) 197-206.
  18. Dantzig, G.B. and Madansky, A. : On the Solution of Two-stage Linear Programs under Uncertainty. Proceedings of The Fourth Berkeley Symposium on Mathematical Statistics and Probability V.1 (1961) 165-176.
  19. Dantzig, G.B. and Infanger, G. : Large-Scale Stochastic Linear Programs-Importance Sampling and Benders Decomposition, Computational and Applied Mathematics I 111-120.
  20. Dantzig, G.B. and Infabger, G. : Large-Scale Stochastic Linear Programs - Importance Sampling and Benders Decomposition, Computational and Applied Mathemativs I (eds, Brezinski, C. and Kualish, U.) 1992 IMACS, p.111-119.
  21. Dempster, M.A.H. : On Stochastic Programming I : Static Linear Programming under Risk.
  22. Dempster, M.A.H. : On Stochastic Programming II ; Dynamic Problems Under Risk, Stochastics 25 (1988) 15-42.
  23. Dragomirescu, M. : An Algorithm for the Minimum-Risk Problem of Stochastic Programming. Operations Research 20 (1972) 154-164.
  24. Dupacova, J. and Wets, R.J.-B. : Asymptotic Behavior of Statistical Estimators and of Optimal Soltuions of Stochastic Optimization Problems The Annals of Statistics 16 (1988) 1517-1549.
  25. Edirisinghe, N.C.P. and Ziemba, W.T. : Tight Bound for Stochastic Convex Programs, Operations Research 40 (1992) 660-677.
  26. Edirisinghe, N.C.P. and Ziemba, W.T. : Bounds for Two-Stage Stochastic Programs with Fixed Recourse, Mathematics of Operation Research 19 (1994) 292-313.
  27. Edirisinghe, N.C.P. and Ziemba, W.T. : Bounding the Expectation of a Saddle Function with Application to Stochastic Programming, Mathematics of Operation Research 19 (1994) 314-340.
  28. Eisner, M.J. and Olsen, P. : Duality for Stochastic Programming Interpreted as LP in $L_{p}$ Space. SIAM Journal of Applied Mathematics 28 (1975) 779-792.
  29. Elmagbraby, S.E. : An Approach to Linear Programming under Uncertainty. Operations Research 7 (1959) 208-216.
  30. Ewbank, J.B., Foote, B.L. and Kumin, H.J. : A Method for the Solution of the Distribution Problem of Stochastic Linear Programming. SIAM Journal of Applied Mathematics 26 \#2 (1974) 225-238.
  31. Ferreira, A.G. and Zerovnik, J. : Bounding the Probability of Success of Stochastic Methods for Global Optimization, Computers Math. Applic. 25 (1993) 1-8.
  32. Flam, S.D. : Lagrange Multipliers in Stochastic Programming. SIAM Journal of Control and Optimization 30 (1992) 1-10.
  33. Frauendorfer, K. : Solving SLP Recourse Problems with Arbitrary Multivariate Distributions - The Dependent Case. Mathematics of Operations Research 13 (1988) 377-394.
  34. Frauendorfer, K. : Multistage Stochastic Programming : Error Analysis for the Convex Case, ZOR 39 (1994) 93-122.
  35. Garstka, S.J. and Rutenberg, D.P. : Computation in Discrete Stochastic Programs with Recourse. Operations Research 21 (1973) 112-122.
  36. Garstka, S.J. and Wets, R.J.-B. : On Decision Rules in Stochastic Programming Mathematical Programming 7 (1974) 117-143.
  37. Garstka, S.J. and Rutenberg, D.P. : Computation in Discrete Stochastic Programs with Recourse, Operations Research 21 (1973) 112-122.
  38. Gelfand, S.B. and Mitter, S.K. : Recursive Stochastic Algorithms for Global Optimization in ${\bf R}^{d}$, SIAM J. Control and Optimization 29 (1991) 999-1018.
  39. Gondzio, J. and Ruszczynski, A. : Sensitivity Method for Basis Inverse Representation in Multistage Stochastic Linear Programming Problems, J Optimization Theory Appl. 74 (1992) 221-242.
  40. Henig, M.I. : Risk Criteria in a Stochastic Knapsack Problem, Operations Research 38 (1990) 820-825.
  41. Hesselbo, B. and Stinchcombe, R.B. : Monte Carlo Simulation and Global Optimization without Parameters, Physical Review Letters 74 (1995) 2151-2155.
  42. Higle, J.L. and Sen, S. : Stochastic Decomposition : An Algotithm for Two-stage Linear Programs with Recourse. Mathematics of Operations Research 16 (1991) 650-669.
  43. Higle, J.L. and Sen, S. : Finite Master Programs in Regularized Stochastic Decomposition, Mathematical Programming 67 (1994) 143-168.
  44. Higle, J.L. and Sen, S. : Stochastic Decomposition : An Algorithm for Two-Stage Linear Programs with Recourse, Mathematics of Operations Research 16 (1991) 650-669.
  45. Hillier, F.S. : Chance-Constrained Programming with 0-1 or Bounded Continuous Decison Variables. Management Science 14 (1967) 34-57.
  46. Holmberg, K. and Jornsten, K.O. : Cross Decomposition Applied to the Stochastic Transportation Problem, European Journal of Operational Research 17 (1984) 361-368.
  47. Ishii, H. and Nishida, T. : Stochastic Linear Knapsack Problem : Probability Maximization Model, Math. Japonica 29 (1984) 273-281.
  48. Jagannathan, R. : Chance-Constrained Programming with Joint Constraints. Operations Research 22 (1974) 358-372.
  49. Jessup, E.P., Yang, O. and Zenios, S.A. : Parallel Factorization of Strucutred Matrices Arising in Stochastic Programming, SIAM J. Optim. 4 (1994) 833-846.
  50. Kataoka, S. : A Stochastic Programming Model. Econometrica 31 (1963) 181-196.
  51. King, A.J. and Wets, R.J.-B. : Epi-consistency of Convex Stochastic Programs. Stochastics and Stochastics Reports 34 (1991) 83-92.
  52. King, A.J. and Rockafellar, R.T. : Asymptotic Theory for Solutions in Statistical Estimation and Stochastic Programming, Mathematics of Operation Research 18 (1993) 148-162.
  53. Kushner, H.J. : Neceaasry Conditions for Continuous Parameter Scochastic Optimization Problems, SIAM J. Control 10 9172) 550-565.
  54. Laporte, G. and Louveaux, F.V. : Then Integer L-Shaped Method for Stochastic Integer Programs with Complete Recourse, Operations Research Letters 13 (1993) 133-142.
  55. Leclercq, J.-P. : Stochastic Programming : An Interactive Multicriteria Approach. European Journal of Operations Research 10 (1982) 33-41.
  56. Lepp, R. : Approximations to Stochastic Programs with Complete Recourse. SIAM Journal of Control and Optimization 28 (1990) 382-394.
  57. Li, X. and Wang, J. : Approximate Feasible Direction Method for Stochastic Programming Problems with Recourse. Linear Inequality Deterministic Constraints. Optimization 21 (1990) 401-407.
  58. Louveaux, F.V. and van der Vlerk, M.H. : Stochastic Programming with Simple Integer Recourse, Mathematical Programming 61 (1993) 301-325.
  59. Mandansky, A. : Dual Variables in Two-Stage Linear Programming under Uncertainty, J. Math. Anal. Appl. 6 (1983) 98-108.
  60. Mangasarian, O.L. and Rosen, J.B. : Inequalities for Stochastic Nonlinear Programming Problems, Operations Research 12 (1964) 143-154.
  61. Mockus, J.B. and Mockus, L.J. : Bayesian Approach to Global Optimization and Application to Multiobjective and Contrained Problems. J. Optim. Theory and Appl. 70 (1991) 157-172.
  62. Morita, H., Ishii, H. and Nishida, T. : Stochastic Linear Knapsack Programming Problem and Its Application to a Portfolio Selection Problem, European J. Operational Research 40 (1989) 329-336.
  63. Morton, D.P. and Wood, R.K. : On a Stochastic Knapsack Problem and Generalizations.
  64. Olsen, P. : Multistage Stochastic Programming with Recourse : The Equivalent Deterministic Problem. SIAM J. Control and Optimization 14 (1976) 495-517.
  65. Olsen, P. : When is Multistage Stochastic Programming Problem Well-defined ? SIAM J. Control and Optimization 14 (1976) 518-527.
  66. Olsen, P. : Multistage Stochastic Programming with Rescourse as Mathematical Programming in an $L_{p}$ Space. SIAM J. Control and Optimization 14 (1976) 528-537.
  67. Piccioni, M. : A Combined Multistart-Annealing Algorithms for Continuous Global Optimization, Computers Math. Applic. 21 (1991) 173-179.
  68. Rockafellar, R.T. and Wets, R.J.-B. : Scenarios and Policy Aggregation in Optimization under Uncertainty. Mathematics of Operations Research 16 (1991) 119-147.
  69. Rockafellar, R.T. and Wets, R.J.-B. : Continuous versus Measurable Recourse in N-Stage Stochastic Programming, J. Math. Anal. Appl. 48 (1974) 836-859.
  70. Rockafellar, R.T. and Wets, R.J.-B. : Stochastic Convex Programming : Kuhn-Tucker Conditions, J. Mathematical Economics 2 (1975) 349-370.
  71. Rockafellar, R.T. and Wets, R.J.-B. : Nonanticipativity and ${\cal L}^{1}$-Martihgales in Stochastic Optimization Problems, Mathematical Programming Study 6 (1976) 170-187.
  72. Rockafellar, R.T. and Wets, R.J.-B. : Stochastic Convex Programming : Basic Duality, Pacific J. Math. 62 (1976) 173-195.
  73. Rockafellar, R.T. and Wets, R.J.-B. : Stochastic Convex Programming : Singular Multipliers and Extended Duality, Pacific J. Math. 62 (1976) 507-522.
  74. Rockafellar, R.T. and Wets, R.J.-B. : Stochastic Convex Programming : Relatively Complete Recourse and Induced Feasibility, SIAM J. Control and Optimization 14 (1976) 574-589.
  75. Rockafellar, R.T. and Wets, R.J.-B. : Measures as Lagrange Multipliers in Multistage Stochastic Programming, J. Math. Anal. Appl. 60 (1977) 301-313.
  76. Rockafellar, R.T. and Wets, R.J.-B. : The Optimal Recourse Problem in Discrete Time : ${\cal L}^{1}$-Multipliers for Inequality Constraints, SIAM J. Control and Optimization 16 (1978) 16-36.
  77. Rockafellar, R.T. and Wets, R.J.-B. : On the Interchange of Subdifferentiation and Conditional Expectation for Convex Funtionals, Stochastics 7 (1982) 173-182.
  78. Rockafellar, R.T. and Wets, R.J.-B. : Generalized Linear-Quadratic Problems of Deterministic and Stochastic Optimal Control in Discrete Time, SIAM J. Control and Optimization 28 (1990) 810-822.
  79. Rockafellar, R.T. and Wets, R.J.-B. : Scenarios and Policy Aggregation in Optimization under Uncertainty, Mathematics of Operation Research 16 (1991) 119-147.
  80. Romisch, W. and Schultz, R. : Distribution Sensitivity in Stochastic Programming. Mathematical Programming 50 (1991) 197-226.
  81. Romisch, W. and Schultz, R. : Stability of Solutions for Stochastic Programs with Complete Recourse, Mathematics of Operation Research 18 (1993) 590-609.
  82. Ruszcynski, A. : Parallel Decomposition of Multistage Stochastic Programming Problems, Mathematical Programming 58 (1993) 201-228.
  83. Schultz, R. : Continuity Properties of Expectation Functions in Stochastic Integer Programming, Mathematics of Operation Research 18 (1993) 578-589.
  84. Sen, S. : Subgradient Decomposiiton and Differentiability of the Recourse Function of a Two Stage Stochastic Linear Program Operations Research Letters 13 (1993) 143-148.
  85. Shapiro, A. : Asymptotic Properties of Statistical Estimators in Stochastic Programming, The Annals of Statitics 17 (1989) 841-858.
  86. Shapiro, A. : Asymptotic Behavior of Optimal Solutions in Stochastic Programming, Mathematics of Operation Research 18 (1993) 829-845.
  87. Shonkwiler, R. and Vleck, E.V. : Parallel Speed-Up of Monte Carlo Methods for Global Optimization, J. Complexity 10 (1994) 64-95.
  88. Sengupta, J.K. : Non-parametric Approach to Stochastic Linear Programming. International Journal of Systems Sciences 24 (1993) 857-871.
  89. Sengupta, J.K., Tintner, G. and Morrison, B. : Stochastic Linear Programming with Applications to Economic Models, Economica 30 (1963) 262-276.
  90. Slyke, R.M.V. and Wets, R. : Programming under Uncertainty and Stochastic Optimal Control. J. SIAM Control 4 (1966) 179-193.
  91. Slyke, R.M.V. and Wets, R. : L-Shaped Liner Programs with Applications to Optimal Control and Stochastic Programming. SIAM Journal of Applied Mathematics 17 (1969) 638-663.
  92. Sniedovich, M. : Preference Order Stochastic Knapsack Problems : Methodological Issues, J. Operational Research Society 31 (1980) 1025-1032.
  93. Steinberg, E. and Parks, M.S. : A Preference Order Dynamic Program for a Knapsack Problem with Stochastic Rewards, J. Operational Research Society 30 (1979) 141-147.
  94. Stolc, L. : Stochastic Linear Programming Method for Right-Hand Sides Random Vector. International Journal of Systems Sciences 22 (1991) 1197-1208.
  95. Swierniak, A.P. : On Optimality in an Uncertain Environment, J. Optimization Theory and Applications 71 (1991) 189-193.
  96. Symond, G.H. : Chance-Constrained Equivalents of Some Stochastic Programming Problems, Operations Research 16 (1968) 1152-1159.
  97. Teghem, J., Dufrane, D. and Thauvoye, M. : STRANGE : An Interative Method for Multi-objective Linear Programming under Unceratinty, European J. Operational Research 26 (1986) 65-82.
  98. Tintner, G. : A Note on Stochastic Linear programming, Econometrica 28 (1960) 490-495.
  99. Todd, M.J. : Probabilistic Models for Linear Programming, Mathematics of Operations Research 16 (1991) 671-693.
  100. Walkup, D.W. and Wets, R.J.-B. : Stochastic Programs with Recourse. SIAM J. Appl. Math. 15 (1967) 1299-1315.
  101. Walkup, D.W. and Wets, R. J.-B. : A Note on Decision Rules for Stochastic Programs, J. Computer and System Sciences 2 (1968) 305-311.
  102. Walkup, D.W. and Wets, R.J.-B. : Stochastic Programs with Recourse II : On the Continuity of the Objective. SIAM J. Appl. Math. 17 (1969) 98-103.
  103. Wallace, S.W. and Yan, T. : Bounding Multi-Stage Stochastic Programs from Above, Mathematical Programming 61 (1993) 111-129.
  104. Wang, J. : Continuity of the Feasible Solution Sets of Probabilistic Constrained Programs. Journal of Optimization and Applications 63 (1989) 79-89.
  105. Watanabe, T. and Ellis, H. : Robustness in Stochastic Programming Models, Appl. Math. Modelling 17 (1993) 547-554.
  106. Wets, R.J.B. : Programming under Uncertainty : The Equivalent Convex Program. SIAM Journal of Applied Mathematics 14 \#1 (1966) 89-105.
  107. Wets, R.J.B. : Programming under Uncertainty : The Solution Set. SIAM Journal of Applied Mathematics 14 \#5 (1966) 1143-1151.
  108. Wets, R.J.-B. : Stochastic Programs with Fixed Recourse : The Equivalent Deterministic Program. SIAM Review 16 (1974) 309-339.
  109. Wets, R.J.-B. : Solving Stochastic Programs with Simple Recourse. Stochastics 10 (1983) 219-242.
  110. Wets, R.J.-B. : Challenges in Stochastic Programming, Mathematical Programming 75 (1996) 115-135.
  111. White, D.J. : A Min-Max-Max-Min Approach to Solving a Stochastic Programming Problem with Simple Recourse. Management Science 38 (1992) 540-554.
  112. Williams, A.C. : On Stochastic Linear Programming, SIAM J. Appl. Math. 13 (1965) 927-940.
  113. Williams, A.C. : Approximation Formulas for Stochastic Linear Programming, SIAM J. Appl. Math. 14 (1966) 668-677.
  114. Wright, S.E. : Primal-Dual Aggregation and Disaggregation for Stochastic Linear Programs, Mathematics of Operation Research 19 (1994) 893-908.