×

Risk aversion in two-stage stochastic integer programming. (English) Zbl 1246.90111

Infanger, Gerd (ed.), Stochastic programming. The state of the art. In honor of George B. Dantzig. New York, NY: Springer (ISBN 978-1-4419-1641-9/hbk; 978-1-4419-1642-6/ebook). International Series in Operations Research & Management Science 150, 165-187 (2011).
In this chapter the author considers the random optimization problem \[ \min \{c^{T}x+q^{T}y+q^{\prime T}y^{\prime }:Tx+Wy+W^{\prime }y^{\prime }=z\left( \omega \right) ,x\in X,y\in \mathbb{Z}_{+}^{\bar{m}},y^{\prime }\in \mathbb{R}_{+}^{m^{\prime }}\},(1) \] where the ingredients of (1) have conformable dimensions, \(W,W^{\prime }\) are rational matrices, and \(X\subseteq \mathbb{R}^{m}\) is a nonempty polyhedron, possibly involving integer requirements to components of \(x.\) He survey structural and algorithmic results for optimization problems which result from (1) (the expectation model, riskaversion model and mean-risk model).
For the entire collection see [Zbl 1203.90008].

MSC:

90C15 Stochastic programming
Full Text: DOI

References:

[1] Ahmed, S., Convexity and decomposition of mean-risk stochastic programs, Math. Program., 106, 3, 433-446 (2006) · Zbl 1134.90025 · doi:10.1007/s10107-005-0638-8
[2] Alonso-Ayuso, A.; Escudero, L. F.; Garín, A.; Ortuño, M. T.; Pérez, G., An approach for strategic supply chain planning under uncertainty based on stochastic 0-1 programming, J. Global Optim., 26, 1, 97-124 (2003) · Zbl 1116.90383 · doi:10.1023/A:1023071216923
[3] Alonso-Ayuso, A.; Escudero, L. F.; Ortuño, M. T., BFC: A branch-and-fix coordination algorithmic framework for solving some types of stochastic pure and mixed 0-1 programs, Eur. J. Oper. Res., 151, 3, 503-519 (2003) · Zbl 1053.90101 · doi:10.1016/S0377-2217(02)00628-8
[4] Artzner, P.; Delbaen, F.; Eber, J.-M.; Heath, D.; Ku, H., Coherent multiperiod risk adjusted values and bellman’s principle, Ann. Oper. Res., 152, 1, 5-22 (2007) · Zbl 1132.91484 · doi:10.1007/s10479-006-0132-6
[5] Bank, B.; Mandel, R., Parametric Integer Optimization (1988), Berlin: Akademie-Verlag, Berlin · Zbl 0643.90043
[6] Bank, B.; Guddat, J.; Klatte, D.; Kummer, B.; Tammer, K., Non-linear Parametric Optimization (1982), Berlin: Akademie-Verlag, Berlin
[7] Bereanu, B., Programme de risque minimal en programmation linéaire stochastique, Comptes Rendus de l’ Académie des Sciences Paris, 259, 5, 981-983 (1964) · Zbl 0123.37301
[8] Bereanu, B., Minimum risk criterion in stochastic optimization, Econ. Comput. Econ. Cybern. Stud. Res., 2, 31-39 (1981) · Zbl 0457.90058
[9] Billingsley, P., Convergence of Probability Measures (1968), New York, NY: Wiley, New York, NY · Zbl 0172.21201
[10] Birge, J. R.; Louveaux, F., Introduction to Stochastic Programming (1997), New York, NY: Springer, New York, NY · Zbl 0892.90142
[11] Blair, C. E.; Jeroslow, R. G., The value function of a mixed integer program: I, Discr. Math., 19, 121-138 (1977) · Zbl 0364.90074 · doi:10.1016/0012-365X(77)90028-0
[12] Bonnans, J. F.; Shapiro, A., Perturbation Analysis of Optimization Problems (2000), New York, NY: Springer, New York, NY · Zbl 0966.49001
[13] Carøe, C. C.; Schultz, R., Dual decomposition in stochastic integer programming, Oper. Res. Lett., 24, 1-2, 37-45 (1999) · Zbl 1063.90037 · doi:10.1016/S0167-6377(98)00050-9
[14] Charnes, A.; Cooper, W. W., Deterministic equivalents for optimizing and satisficing under chance constraints, Oper. Res., 11, 1, 18-38 (1963) · Zbl 0117.15403 · doi:10.1287/opre.11.1.18
[15] Dentcheva, D.; Römisch, W., Duality gaps in nonconvex stochastic optimization, Math. Program., 101, 3, 515-535 (2004) · Zbl 1073.90025 · doi:10.1007/s10107-003-0496-1
[16] Dentcheva, D.; Ruszczyński, A., Stochastic optimization with dominance constraints, SIAM J. Optim., 14, 2, 548-566 (2003) · Zbl 1055.90055 · doi:10.1137/S1052623402420528
[17] Dentcheva, D.; Ruszczyński, A., Optimality and duality theory for stochastic optimization with nonlinear dominance constraints, Math. Program., 99, 2, 329-350 (2004) · Zbl 1098.90044 · doi:10.1007/s10107-003-0453-z
[18] Eichhorn, A.; Römisch, W., Polyhedral risk measures in stochastic programming, SIAM J. Optim., 16, 1, 69-95 (2005) · Zbl 1114.90077 · doi:10.1137/040605217
[19] Helmberg, C.; Kiwiel, K. C., A spectral bundle method with bounds, Math. Program., 93, 7, 173-194 (2002) · Zbl 1065.90059 · doi:10.1007/s101070100270
[20] Kall, P.; Wallace, S. W., Stochastic Programming (1994), Chichester: Wiley, Chichester · Zbl 0812.90122
[21] Kibzun, A. I.; Kan, Y. S., Stochastic Programming Problems with Probability and Quantile Functions (1996), Chichester: Wiley, Chichester · Zbl 0885.90088
[22] Kiwiel, K. C., Proximity control in bundle methods for convex nondifferentiable optimization, Math. Program., 46, 1-2, 105-122 (1990) · Zbl 0697.90060 · doi:10.1007/BF01585731
[23] Kristoffersen, T., Deviation measures in linear two-stage stochastic programming, Math. Methods Oper. Res., 62, 2, 255-274 (2005) · Zbl 1109.90065 · doi:10.1007/s00186-005-0006-8
[24] Levy, H., Stochastic dominance and expected utility: survey and analysis, Manage. Sci., 38, 4, 555-593 (1992) · Zbl 0764.90004 · doi:10.1287/mnsc.38.4.555
[25] Louveaux, F. V.; Schultz, R.; Ruszczyński, A.; Shapiro, A., Stochastic integer programming., Stochastic Programming, Handbooks in Operations Research and Management Science, 213-266 (2003), Amsterdam: Elsevier, Amsterdam · Zbl 1115.90001 · doi:10.1016/S0927-0507(03)10004-7
[26] Märkert, A.; Schultz, R., On deviation measures in stochastic integer programming, Oper. Res. Lett., 33, 5, 441-449 (2005) · Zbl 1099.90037 · doi:10.1016/j.orl.2004.09.003
[27] Markowitz, H. M., Portfolio selection, J. Finance, 7, 1, 77-91 (1952)
[28] Müller, A.; Stoyan, D., Comparison Methods for Stochastic Models and Risks (2002), Chichester: Wiley, Chichester · Zbl 0999.60002
[29] Mulvey, J. M.; Vanderbei, R. J.; Zenios, S. A., Robust optimization of large-scale systems, Oper. Res., 43, 2, 264-281 (1995) · Zbl 0832.90084 · doi:10.1287/opre.43.2.264
[30] Ogryczak, W.; Ruszczyński, A., From stochastic dominance to mean-risk models: Semideviations as risk measures, Eur. J. Oper. Res., 116, 1, 33-50 (1999) · Zbl 1007.91513 · doi:10.1016/S0377-2217(98)00167-2
[31] Ogryczak, W.; Ruszczyński, A., Dual stochastic dominance and related mean-risk models, SIAM J. Optim., 13, 1, 60-78 (2002) · Zbl 1022.91017 · doi:10.1137/S1052623400375075
[32] Pflug, G. C.; Uryasev, S., Some remarks on the value-at-risk and the conditional value-at-risk., Probabilistic Constrained Optimization: Methodology and Applications, 272-281 (2000), Dordrecht: Kluwer, Dordrecht · Zbl 0994.91031
[33] Pflug, G. C., A value-of-information approach to measuring risk in multiperiod economic activity, J. Bank. Finance., 30, 2, 695-715 (2006) · doi:10.1016/j.jbankfin.2005.04.006
[34] Pflug, G. C.; Ruszczyński, A.; Szegö, G., Risk measures for income streams., Risk Measures for the 21st. Century, 249-269 (2004), Chichester: Wiley, Chichester
[35] Prékopa, A., Stochastic Programming (1995), Dordrecht: Kluwer, Dordrecht · Zbl 0863.90116
[36] Raik, E., Qualitative research into the stochastic nonlinear programming problems, Eesti NSV Teaduste Akademia Toimetised / Füüsika, Matemaatica (News of the Estonian Academy of Sciences / Physics, Mathematics), 20, 8-14 (1971) · Zbl 0219.90038
[37] Raik, E., On the stochastic programming problem with the probability and quantile functionals, Eesti NSV Teaduste Akademia Toimetised / Füüsika, Matemaatica (News of the Estonian Academy of Sciences / Physics, Mathematics), 21, 142-148 (1972) · Zbl 0243.90030
[38] Riis, M.; Schultz, R., Applying the minimum risk criterion in stochastic recourse programs, Comput. Optim. Appl., 24, 2-3, 267-287 (2003) · Zbl 1094.90028 · doi:10.1023/A:1021862109131
[39] Robinson, S. M., Local epi-continuity and local optimization, Math. Program., 37, 2, 208-222 (1987) · Zbl 0623.90078 · doi:10.1007/BF02591695
[40] Rockafellar, R. T.; Uryasev, S., Conditional value-at-risk for general loss distributions, J. Bank. Finance., 26, 7, 1443-1471 (2002) · doi:10.1016/S0378-4266(02)00271-6
[41] Römisch, W.; Ruszczyński, A. A.; Shapiro, A., Stability of stochastic programming problems., Stochastic Programming, Handbooks in Operations Research and Management Science, 483-554 (2003), Amsterdam: Elsevier, Amsterdam · Zbl 1115.90001 · doi:10.1016/S0927-0507(03)10008-4
[42] Ruszczyński, A.; Shapiro, A., Stochastic Programming. Handbooks in Operations Research and Management Science (2003), Amsterdam: Elsevier, Amsterdam · Zbl 1115.90001
[43] Ruszczyński, A.; Vanderbei, R. J., Frontiers of stochastically nondominated portfolios, Econometrica, 71, 4, 1287-1297 (2003) · Zbl 1154.91475 · doi:10.1111/1468-0262.t01-1-00448
[44] Schultz, R., On structure and stability in stochastic programs with random technology matrix and complete integer recourse, Math. Program., 70, 1-3, 73-89 (1995) · Zbl 0841.90101
[45] Schultz, R., Some aspects of stability in stochastic programming, Ann. Oper. Res., 100, 1-4, 55-84 (2000) · Zbl 1017.90073 · doi:10.1023/A:1019258932012
[46] Schultz, R.; Jünger, M.; Reinelt, G.; Rinaldi, G., Mixed-integer value functions in stochastic programming., Combinatorial Optimization - Eureka, You Shrink!, 171-184 (2003), Berlin: Springer, Berlin · Zbl 1024.90051 · doi:10.1007/3-540-36478-1_16
[47] Schultz, R.; Tiedemann, S., Risk aversion via excess probabilities in stochastic programs with mixed-integer recourse, SIAM J. Optim., 14, 1, 115-138 (2003) · Zbl 1043.90059 · doi:10.1137/S1052623402410855
[48] Schultz, R.; Tiedemann, S., Conditional value-at-risk in stochastic programs with mixed-integer recourse, Math. Program., 105, 2-3, 365-386 (2006) · Zbl 1085.90042 · doi:10.1007/s10107-005-0658-4
[49] Takriti, S.; Ahmed, S., On robust optimization of two-stage systems, Math. Program., 99, 1, 109-126 (2004) · Zbl 1111.90080 · doi:10.1007/s10107-003-0373-y
[50] Tiedemann, S.: Risk measures with preselected tolerance levels in two-stage stochastic mixed-integer programming. PhD thesis, University of Duisburg-Essen, Cuvillier Verlag, Göttingen (2005)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.