Two-stage stochastic programs: Integer variables, dominance relations and PDE constraints

Rüdiger Schultz

doi:10.3934/naco.2012.2.713

Article Contents

2012, Volume 2, Issue 4: 713-738. Doi: 10.3934/naco.2012.2.713

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Two-stage stochastic programs: Integer variables, dominance relations and PDE constraints

Rüdiger Schultz^1,

1.
Department of Mathematics, University of Duisburg-Essen, Campus Duisburg, Lotharstr. 65, D-47048 Duisburg

Received: December 2011

Revised: November 2012

Published: November 2012

Abstract / Introduction Related Papers Cited by

Abstract

From a unified point-of-view, we present some recent developments in two-stage stochastic programming. Our discussion includes stochastic programs with integer variables, stochastic programs with dominance constraints, and PDE constrained stochastic programs.

Keywords:

Mathematics Subject Classification: Primary: 90C15, 90C11, 60E15.

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References

[1]	B. Bank, J. Guddat, D. Klatte, B. Kummer and K. Tammers, "Non-linear Parametric Optimization," Akademie-Verlag, Berlin, 1983.
[2]	B. Bank and R. Mandel, "Parametric Integer Optimization," Akademie-Verlag, Berlin 1988.
[3]	A. Ben-Tal, L. El-Ghaoui and A. Nemirovski, "Robust Optimization," Princeton University Press, Princeton and Oxford, 2009.
[4]	J. R. Birge and F. Louveaux, "Introduction to Stochastic Programming," Springer-Verlag, New York, 1997.
[5]	C. E. Blair and R. G. Jeroslow, The value function of a mixed integer program: I, Discrete Mathematics, 19 (1977), 121-138.
[6]	C. C. Carøe and R. Schultz, Dual decomposition in stochastic integer programming, Operations Research Letters, 24 (1999), 37-45.
[7]	M. Carrión, U. Gotzes and R. Schultz, Risk aversion for an electricity retailer with second-order stochastic dominance constraints, Computational Management Science, 6 (2009), 233-250.
[8]	P. G. Ciarlet, "Mathematical Elasticity Volume I: Three-Dimensional Elasticity," Studies in Mathematics and its Applications, Vol. 20, North-Holland, 1988.
[9]	CPLEX Callable Library-9.1.3, ILOG, 2008. Available from: http://www-01.ibm.com/software/integration/optimization/cplex-optimizer/.
[10]	S. Conti, H. Held, M. Pach, M. Rumpf and R. Schultz, Shape optimization under uncertainty - a stochastic programming perspective, SIAM Journal on Optimization, 19 (2008), 1610-1632.
[11]	S. Conti, H. Held, M. Pach, M. Rumpf and R. Schultz, Risk averse shape optimization, SIAM Journal on Control and Optimization, 49 (2011), 927-947.
[12]	M. C. Delfour and J. P. Zolésio, "Shapes and Geometries: Analysis, Differential Calculus and Optimization," SIAM, Philadelphia, 2001.
[13]	D. Dentcheva and A. Ruszczyński, Optimization with stochastic dominance constraints, SIAM Journal on Optimization, 14 (2003), 548-566.
[14]	D. Dentcheva and A. Ruszczyński, Optimality and duality theory for stochastic optimization with nonlinear dominance constraints, Mathematical Programming, 99 (2004), 329-350.doi: 10.1007/s10107-003-0453-z.
[15]	R. Gollmer, U. Gotzes and R. Schultz, A note on second-order stochastic dominance constraints induced by mixed-integer linear recourse, Mathematical Programming, 127 (2011), 179-190.
[16]	R. Gollmer, F. Neise and R. Schultz, Stochastic programs with first-order dominance constraints induced by mixed-integer linear recourse, SIAM Journal on Optimization, 19 (2008), 552-571.
[17]	U. Gotzes and F. Neise, "User's Guide to ddsip.vSD - A C Package for the Dual Decomposition of Stochastic Programs with Dominance Constraints Induced by Mixed-Integer Linear Recourse," Department of Mathematics, University of Duisburg-Essen, 2008.
[18]	E. Handschin, F. Neise, H. Neumann and R. Schultz, Optimal operation of dispersed generation under uncertainty using mathematical programming, International Journal of Electrical Power & Energy Systems, 28 (2006), 618-626.
[19]	A. Märkert and R. Gollmer, "User's Guide to ddsip - A C Package for the Dual Decomposition of Two-Stage Stochastic Programs with Mixed-Integer Recourse," Department of Mathematics, University of Duisburg-Essen, 2008; Available from: http://www.neos-server.org/neos/solvers/slp:ddsip/MPS.html.
[20]	A. Müller and D. Stoyan, "Comparison Methods for Stochastic Models and Risks," Wiley, Chichester, 2002.
[21]	G. L. Nemhauser and L. A. Wolsey, "Integer and Combinatorial Optimization," Wiley, New York 1988.
[22]	A. Prékopa, "Stochastic Programming," Kluwer, Dordrecht, 1995.
[23]	A. Ruszczyński and A. Shapiro, "Stochastic Programming," Handbooks in Operations Research and Management Science, Elsevier, Amsterdam, 10 (2003).
[24]	R. Schultz, Continuity properties of expectation functions in stochastic integer programming, Mathematics of Operations Research, 18 (1993), 578-589.
[25]	R. Schultz, On structure and stability in stochastic programs with random technology matrix and complete integer recourse, Mathematical Programming, 70 (1995), 73-89.
[26]	R. Schultz, Stochastic programming with integer variables, Mathematical Programming, 97 (2003), 285-309.
[27]	R. Schultz and S. Tiedemann, Risk Aversion via Excess Probabilities in Stochastic Programs with Mixed-Integer Recourse, SIAM Journal on Optimization, 14 (2003), 115-138.
[28]	A. Shapiro, D. Dentcheva and A. Ruszczyński, "Lectures on Stochastic Programming: Modeling and Theory," SIAM-MPS, Philadelphia, 2009.
[29]	J. Sokołowski and J. P. Zolésio, "Introduction to Shape Optimization: Shape Sensitivity Analysis," Springer, 1992.