Maarten H. van der Vlerk
Department of Operations
University of Groningen
PO Box 800, NL-9700 AV Groningen, The Netherlands
E-mail:
October 8, 2007
One of the sources for this bibliography has been
the list of
Books on Stochastic Programming,
compiled by J. Dupacová,
which was first published in Wets and Ziemba [4033].
Please send additions (preferably in
BibTeX
format) or comments to the
e-mail address mentioned above.
This bibliography can be cited as
Maarten H. van der Vlerk. Stochastic Programming Bibliography.
World Wide Web, http://mally.eco.rug.nl/spbib.html,
1996-2007.
The BibTex entry I use is
@MISC{SPB9607,
author = {Maarten H. {van der Vlerk}},
title = {Stochastic Programming Bibliography},
year = {1996-2007},
howpublished = {World Wide Web, \url{http://mally.eco.rug.nl/spbib.html}}
}
where the macro \url is defined in the
LATEX
style file
url.sty.
I.N. Kamal Abadi, Nicholas G. Hall, and Chelliah Sriskandarajah.
Minimizing cycle time in a blocking flowshop.
Oper. Res., 48(1):177-180, 2000.
J. Abaffy and E. Allevi.
A modified L-shaped method.
J. Optim. Theory Appl., 123(2):255-270, 2004.
Moncef Abbas and Fatima Bellahcene.
Cutting plane method for multiple objective stochastic integer linear
programming.
European J. Oper. Res., 168(3):967-984, 2006.
N. E. Abboud, M. Y. Jaber, and N. A. Noueihed.
Economic lot sizing with the consideration of random machine
unavailability time.
Comput. Oper. Res., 27(4):335-351, 2000.
P. Abel.
Decisions in stochastic linear programming models under partial
information.
Z. Angew. Math. Mech. 73, No.7-8, T 737-T 738, 1993.
Peter Abel.
Stochastische Optimierung bei partieller Information,
volume 96 of Mathematical Systems in Economics.
Verlagsgruppe Athenäum/Hain/Hanstein, Königstein/Ts., 1984.
Peter Abel.
Stochastic linear programming with recourse under partial
information.
In Probability and Bayesian statistics (Innsbruck, 1986), pages
1-6. Plenum, New York, 1987.
Peter Abel and Reiner Thiel.
Mehrstufige stochastische Produktionsmodelle. Eine
praxisorientierte Darstellung mit programmierten Beispielen.
Schriften zur Quantitativen Wirtschaftsforschung, Bd. 5. Frankfurt am
Main: Rita G. Fischer Verlag., 1981.
Jinane Abounadi, Dimitri P. Bertsekas, and Vivek Borkar.
Stochastic approximation for nonexpansive maps: application to
Q-learning algorithms.
SIAM J. Control Optim., 41(1):1-22 (electronic), 2002.
L.M. Abramov and I.I. Bockareva.
A stochastic programming problem with probabilistic constraints.
Optimal. Planirovanie, 16:3-9, 1970.
G.M. Adamenko.
Solution of extremal problems under conditions of incomplete
information.
Automat. Control Comput. Sci., 14(4):48-55, 1980.
M. Ju. Afanas'ev.
An example of the cycling of a stochastic integer algorithm in a
bilevel multicommodity problem.
In Methods of function analysis in mathematical economics
(Russian), pages 111-114. Izdat. "Nauka", Moscow, 1978.
P. K. Agarwal, B. K. Bhattacharya, and S. Sen.
Improved algorithms for uniform partitions of points.
Algorithmica, 32(4):521-539, 2002.
R.A. Agnew and R.B. Hempley.
Finite statistical games and linear programming.
Naval Res. Logist. Quart. 18, 99-102, 1971.
Saligrama Agnihothri, Uday S. Karmarkar, and Peter Kubat.
Stochastic allocation rules.
Oper. Res. 30, 545-555, 1982.
G.A. Agranovich and L.N. Kanov.
A method of computing the gradient and the Hessian of the quality
criterion in parametric optimization of continuous-discrete stochastic
systems.
J. Math. Sci., 82(3):3412-3415, 1996.
Dynamical systems, No. 13.
Shabbir Ahmed.
Convexity and decomposition of mean-risk stochastic programs.
Math. Program., 106(3, Ser. A):433-446, 2006.
Shabbir Ahmed.
Smooth minimization of two-stage stochastic linear programs.
Optimization Online, http://www.optimization-online.org, 2006.
Shabbir Ahmed, Ulas Cakmak, and Alexander Shapiro.
Coherent risk measures in inventory problems.
Stochastic Programming E-Print Series, http://www.speps.org,
2006.
Shabbir Ahmed, Alan J. King, and Gyana Parija.
A multi-stage stochastic integer programming approach for capacity
expansion under uncertainty.
Stochastic Programming E-Print Series, http://www.speps.org,
2001.
Shabbir Ahmed, Alan J. King, and Gyana Parija.
A multi-stage stochastic integer programming approach for capacity
expansion under uncertainty.
Optimization Online, http://www.optimization-online.org, 2001.
Shabbir Ahmed and Alexander Shapiro.
The sample average approximation method for stochastic programs with
integer recourse.
Optimization Online, http://www.optimization-online.org, 2002.
Shabbir Ahmed, Mohit Tawarmalani, and Nikolaos V. Sahinidis.
A finite branch-and-bound algorithm for two-stage stochastic integer
programs.
Math. Program., 100(2, Ser. A):355-377, 2004.
Shabbir Ahmed, Mohit Tawarmalani, and Nikolas V. Sahinidis.
A finite branch and bound algorithm for two-stage stochastic integer
programs.
Stochastic Programming E-Print Series, http://www.speps.org,
2000.
Byong-Hun Ahn and Bo-Woo Nam.
Multiperiod optimal power plant mix under demand uncertainty.
J. Oper. Res. Soc. Jap. 31, No.3, 353-370, 1988.
M. Aicardi, G. Casalino, F. Davoli, R. Minciardi, and R. Zoppoli.
A decentralized closed-loop solution to the routing problem in
networks.
Annu. Rev. Autom. Program. 13, Part 2, 9-17, 1986.
Z.Zh. Akhmetzhanova and G.M. Bakan.
Solution of a programming problem with inexactly specified initial
data.
Sov. J. Autom. Inf. Sci. 21, No.2, 55-58 translation from
Avtomatika 1988, No.2, 54-56 (1988)., 1988.
Hisham Al-Mharmah and James M. Calvin.
Optimal random non-adaptive algorithm for global optimization of
Brownian motion.
J. Global Optim., 8(1):81-90, 1996.
Hisham A. Al-Mharmah and James M. Calvin.
Comparison of one-dimensional composite and non-composite passive
algorithms.
J. Global Optim., 15(2):169-180, 1999.
Aureli Alabert i Romero.
On the optimization of hydroelectric power generation with random
water inflows.
Qüestiió, 15(3):307-348, 1991.
Chris M. Alaouze and Peter J. Lloyd.
A generalization of Gurland's theorem, with applications to economic
behavior under uncertainty.
Am. Stat. 40, 70-71, 1986.
Horst Albach.
Capital budgeting and risk management.
In Quant. Wirtsch.-Forsch., W. Krelle zum 60. Geb., 7-24,
1977.
Maria Albareda-Sambola and Elena Fernández.
The stochastic generalised assignment problem with Bernoulli
demands.
Top, 8(2):165-190, 2000.
Maria Albareda-Sambola, Maarten H. van der Vlerk, and Elena Fernández.
Exact solutions to a class of stochastic generalized assignment
problems.
European J. Oper. Res., 173(2):465-487, 2006.
Ya. Alber.
Dynamical processes of stochastic approximation.
Funct. Differ. Equ., 4(3-4):239-256 (1998), 1997.
Ya. I. Al'ber and S.V. Shil'man.
Stochastic programming methods: convergence and nonasymptotic
estimation of the convergence rate.
In Stochastic optimization (Kiev, 1984), volume 81 of
Lecture Notes in Control and Inform. Sci., pages 249-257. Springer, Berlin,
1986.
Susanne Albers, Rolf H. Möhring, Georg Ch. Pflug, and Rüdiger Schultz.
05031 Summary - Algorithms for Optimization with Incomplete
Information.
In S. Albers, R.H. Möhring, G.Ch. Pflug, and R. Schultz, editors,
Dagstuhl Seminar 05031: Algorithms for Optimization with Incomplete
Information, http://www.dagstuhl.de/05031, 2005.
V. Albornoz, J. Arrate, and L. Contesse.
Solucion de modelos de dimensionamiento de lotes no capacitados bajo
incertidumbre en las demandas.
Revista del Instituto Chileno de Investigacion Operativa,
6(1-2):52-62, 2001.
V. Albornoz and C. Canales.
Planificacion de la conservacion y explotacion del langostino
colorado usando un modelo de optimizacion estoc stica no-lineal con recurso.
Informacion Tecnologica, 13(4):??, 2002.
V. Albornoz and L. Contesse.
Modelos de optimizacion robusta para un problema de planificacion
agregada de la produccion bajo incertidumbre en las demandas.
Investigacion Operativa, 7(3):1-16, 1999.
A. Albrecht, S.K. Cheung, K.C. Hui, K.S. Leung, and C.K. Wong.
Optimal placements of flexible objects. I. Analytical results for
the unbounded case.
IEEE Trans. Comput., 46(8):890-904, 1997.
A. Albrecht, S.K. Cheung, K.C. Hui, K.S. Leung, and C.K. Wong.
Optimal placements of flexible objects. II. A simulated
annealing approach for the bounded case.
IEEE Trans. Comput., 46(8):905-929, 1997.
S.Christian Albright.
A Markov-decision-chain approach to a stochastic assignment
problem.
Operations Res. 22, 61-64, 1974.
Michael Albritton, Alexander Shapiro, and Mark Spearman.
Finite capacity production planning with random demand and limited
information.
Stochastic Programming E-Print Series, http://www.speps.org,
2000.
David Aldous.
Minimization algorithms and random walk on the d-cube.
Ann. Probab., 11(2):403-413, 1983.
I.A. Aleksandrov, V.P. Bulatov, S.B. Ognivtsev, and F.I. Yereshko.
Solution of a stochastic programming problem concerning the
distribution of water resources.
In Stochastic optimization (Kiev, 1984), volume 81 of
Lecture Notes in Control and Inform. Sci., pages 258-264. Springer, Berlin,
1986.
V.M. Aleksandrov, V.I. Sysoev, and V.V. Semeneva.
Stochastische Optimierung von Systemen.
Izv. Akad. Nauk SSSR, Tekh. Kibern. 1968, No. 5, 14-19, 1968.
A. Alessandri and T. Parisini.
Nonlinear modelling of complex large-scale plants using neural
networks and stochastic approximation.
IEEE Transactions on Systems, Man, and Cybernetics - A,
27:750-757, 1997.
David L. J. Alexander, David Bulger, James M. Calvin, H. Edwin Romeijn, and
Ryan L. Sherriff.
Approximate implementations of pure random search in the presence of
noise.
J. Global Optim., 31(4):601-612, 2005.
M. Montaz Ali, Charoenchai Khompatraporn, and Zelda B. Zabinsky.
A numerical evaluation of several stochastic algorithms on selected
continuous global optimization test problems.
J. Global Optim., 31(4):635-672, 2005.
M.M. Ali and C. Storey.
Topographical multilevel single linkage.
J. Global Optim., 5(4):349-358, 1994.
M.M. Ali, A. Törn, and S. Viitanen.
A numerical comparison of some modified controlled random search
algorithms.
J. Global Optim., 11(4):377-385, 1997.
Montaz M. Ali.
A probabilistic hybrid differential evolution algorithm.
In Models and algorithms for global optimization, volume 4 of
Springer Optim. Appl., pages 173-184. Springer, New York, 2007.
F.M. Allen, R.N. Braswell, and P.V. Rao.
Distribution-free approximations for chance constraints.
Operations Res., 22(3):610-621, 1974.
Sira Allende and Carlos Bouza.
Stochastic programming approaches to the estimation of the mean in
stratified population.
Investigación Oper., 14(2-3):109-118, 1993.
Workshop on Stochastic Optimization: the State of the Art (Havana,
1992).
Sira Allende and Carlos Bouza.
Random demands: optimum lot size and the newsboy problem.
Investigación Oper., 23(3):124-129, 2002.
A. Alonso-Ayuso, L. F. Escudero, C. Pizarro, H. E. Romeijn, and
D. Romero Morales.
On solving the multi-period single-sourcing problem under
uncertainty.
Comput. Manag. Sci., 3(1):29-53, 2006.
Mahmoud H. Alrefaei.
Stochastic optimization using the standard clock simulation.
Int. J. Appl. Math., 8(3):317-333, 2002.
Mahmoud H. Alrefaei and Ameen J. Alawneh.
Solution quality of random search methods for discrete stochastic
optimization.
Math. Comput. Simulation, 68(2):115-125, 2005.
Mahmoud H. Alrefaei and Mohammad Almomani.
Subset selection of best simulated systems.
J. Franklin Inst., 344(5):495-506, 2007.
Mahmoud H. Alrefaei and Sigrún Andradóttir.
A simulated annealing algorithm with constant temperature for
discrete stochastic optimization.
Management Science, 45:748-764, 1999.
Mahmoud H. Alrefaei and Sigrún Andradóttir.
A modification of the stochastic ruler method for discrete stochastic
optimization.
European J. Oper. Res., 133(1):160-182, 2001.
Mahmoud H. Alrefaei and Sigrún Andradóttir.
Discrete stochastic optimization using variants of the stochastic
ruler method.
Naval Res. Logist., 52(4):344-360, 2005.
M.H. Alrefaei and S. Andradóttir.
A new search algorithm for discrete stochastic optimization.
Proceedings of the 1995 Winter Simulation Conference 236-241,
1995.
M.H. Alrefaei and S. Andradóttir.
Discrete stochastic optimization via a modification of the stochastic
ruler method.
Proceedings of the 1996 Winter Simulation Conference 406-411,
1996.
A.Z. Al'terman.
On a realization of random search for the construction of a
separating metric.
Probl. Sluchajnogo Poiska 7, 307-313, 1978.
A. Altman, M. Amann, G. Klaassen, A. Ruszczy\'nski, and W. Schöpp.
Cost-effective sulphur emission under uncertainty.
European Journal of Operational Research, 90:395-412, 1996.
Adel A. Aly and John A. White.
Probabilistic formulations of the multifacility Weber problem.
Naval Res. Logist. Quart., 25(3):531-547, 1978.
Yakov Amihud.
The effect of uncertainty in input quantities on the optimal
expected input combination.
Manage. Sci. 23, 957-962, 1977.
H. M. Amman and D. A. Kendrick.
Stochastic policy design in a learning environment with rational
expectations.
J. Optim. Theory Appl., 105(3):509-520, 2000.
Special Issue in honor of Professor David G. Luenberger.
Hans M. Amman, David A. Kendrick, and Sudhakar Achath.
Solving stochastic optimization models with learning and rational
expectations.
Econom. Lett., 48(1):9-13, 1995.
G. Anandalingam.
A stochastic programming process model for investment planning.
Comput. Oper. Res. 14, 521-536, 1987.
Yu. G. Anastasyan, V.I. Gershovich, B.A. Yaroshevich, È. I. Nenakhov, O.T.
Burlak, M.B. Shchepakin, and G.G. Murauskas.
O nekotorykh algoritmakh negladkoi optimizatsii i
diskretnogo programmirovaniya, volume 6 of Preprint 81.
Akad. Nauk Ukrain. SSR Inst. Kibernet., Kiev, 1981.
E. J. Anderson and A. B. Philpott.
On supply function bidding in electricity markets.
In C. Greengard and A. Ruszczy\'nski, editors, Decision Making
under Uncertainty: Energy and Power, volume 128 of IMA volumes on
Mathematics and its Applications, pages 115-134. Springer-Verlag, 2002.
S. Andradóttir.
A method for discrete stochastic optimization.
Management Science 1946-1961, 1995.
S. Andradóttir.
A stochastic approximation algorithm with varying bounds.
Operations Research 1037-1048, 1995.
S. Andradóttir.
A global search method for discrete stochastic optimization.
SIAM Journal on Optimization 513-530, 1996.
S. Andradóttir.
Optimization of the transient and steady-state behavior of discrete
event systems.
Management Science 717-737, 1996.
S. Andradóttir.
A scaled stochastic approximation algorithm.
Management Science 475-498, 1996.
S. Andradóttir.
Simulation optimization.
Handbook on Simulation (edited by Jerry Banks), Chapter
9, John Wiley and Sons New York, to appear.
Mikhail Andramonov, Jerzy Filar, Panos Pardalos, and Alexander Rubinov.
Hamiltonian cycle problem via Markov chains and min-type
approaches.
In Approximation and complexity in numerical optimization
(Gainesville, FL, 1999), pages 31-47. Kluwer Acad. Publ., Dordrecht, 2000.
G. Andreatta.
Shortest path models in stochastic networks.
In G. Andreatta, F. Mason, and P. Serafini, editors, Stochastics
in Combinatorial Optimization, pages 178-186, Singapore, 1987. CISM,
Udine, World Scientific Publishing Co. Pte. Ltd.
G. Andreatta and F. Mason.
k-Eccentricity and absolute k-centrum of a probabilistic tree.
Eur. J. Oper. Res. 19, 114-117, 1985.
G. Andreatta and G. Romanin-Jacur.
Aircraft flow management under congestion.
Transportation Science, 21(4):249-253, 1987.
G.B. Andreatta, G. Salinetti, and R.J.-B. Wets, editors.
Stochastic programming.
Baltzer Science Publishers BV, Amsterdam, 1995.
Papers from the Sixth International Conference held in Udine,
September 14-18, 1992, Ann. Oper. Res. 56 (1995).
Giovanni Andreatta and Luciano Romeo.
Stochastic shortest paths with recourse.
Networks 18, No.3, 193-204, 1988.
Giovanni Andreatta and Wolfgang J. Runggaldier.
An approximation scheme for stochastic dynamic optimization problems.
Math. Programming Stud., 27:118-132, 1986.
Stochastic programming 84. I.
Colette Andrieu.
Sur les solutions fiables d'un problème stochastique d'optimisation
sous contrainte.
Rev. Roumaine Math. Pures Appl., 25(5):677-694, 1980.
Colette Andrieu.
Sur certaines solutions fiables d'un problème stochastique de
recherche optimale.
Math. Operationsforsch. Statist. Ser. Optim., 12(1):115-122,
1981.
Y.P. Aneja and K.P.K. Nair.
Maximal expected flow in a network subject to arc failures.
Networks 10, 45-57, 1980.
R. Anghelescu and V. Anghelescu.
Recherches sur la programmation lineaire stochastique a recours.
(Research on linear stochastic programming with recourse).
In Proc. Symp. Math. Appl., Timisoara/Rom. 1985, 163-165,
1986.
R. Anghelescu and V. Anghelescu.
étude sur la programmation linéaire stochastique.
In Proceedings of the Second Symposium of Mathematics and its
Applications (Timi soara, 1987), pages 217-220, Timi soara, 1988. Res.
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R. Anghelescu and V. Anghelescu.
Modalités d'approche des problèmes stochastiques d'optimum
vectoriel. I.
In Proceedings of the Third Symposium of Mathematics and its
Applications (Timi soara, 1989), pages 123-128, Timi soara, 1990. Rom.
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R. Anghelescu and V. Anghelescu.
Solution optimale dans la programmation stochastique vectorielle.
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In Proceedings of the Fourth Symposium of Mathematics and its
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Rodica Anghelescu and V. Anghelescu.
Methods in determinating the optimal solution in problems of linear
stochastic programming.
Bul. Stiin t. Tehn. Univ. Tehn. Timi soara Mat. Fiz.,
38(52):94-101, 1993.
Z.P. Anisimova and O.R. Petrenko.
Limit theorems of stochastic optimization procedures in Markov
random environments.
In Stochastic systems and their applications (Russian), pages
4-8. Akad. Nauk Ukrain. SSR Inst. Mat., Kiev, 1990.
A.N. Antamoshkin and M.A. Valishevskij.
Complete effectivity investigation of methods optimizing functionals
with Boolean derivatives taking random search as example.
In Applications of random search to the solution of applied
problems, Collect. sci. Works, Kemerovo 1982, 48-54, 1982.
K.A. Antanavichyus and S.S. Chirba.
A stochastic programming problem for preparing rational production
programs for branch complexes.
Ehkon. Mat. Metody 21, 1048-1057, 1985.
K.A. Antanavichyus and S.S. Chirba.
A problem of stochastic programming for preparation of rational
production programs for branch complexes.
Èkonom. i Mat. Metody, 21(6):1048-1057, 1985.
P.L. Antonelli and J.M. Skowronski.
Adaptive identification of environmental stress for the management
of plant growth.
Math. Comput. Modelling 10, No.1, 27-35, 1988.
G.E. Antonov and V. Ja. Katkovnik.
A generalization of the concept of statistical gradient.
Avtomat. i Vycisl. Tehn. (Riga), 4:25-30, 1972.
I.L. Antonov.
A steady-state process in a two-dimensional extremal system in the
presence of prohibited regions and a random method of search.
Vestnik Moskov. Univ. Ser. I Mat. Meh., 25(5):117-122, 1970.
I.L. Antonov.
A transition process in a two-dimensional extremal system in the
presence of forbidden domains, in a random method of search.
In Problems of statistical optimization (Russian), pages
69-80. Izdat. "Zinatne", Riga, 1971.
Bruno Apolloni and Ferdinando Pezzella.
Confidence intervals in the solution of stochastic integer linear
programming problems.
In Stochastics and optimization, Sel. Pap. ISSO Meet.,
Gorguano/Italy 1982, Ann. Oper. Res. 1, 67-78, 1984.
N.I. Arbuzova.
Ueber die stochastische .-Stabilitaet der Loesung einer Aufgabe
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Izv. Akad. Nauk SSSR, tehn. Kibernet. 1967, Nr. 3, 35-40, 1967.
N.I. Arbuzova.
Interdependence of the stochastic e-stabilities of linear
and linear fractional programming problems of a special form.
Èkonom. i Mat. Metody, 4:108-110, 1968.
N.I. Arbuzova and V.L. Danilov.
Zur Erweiterung des Begriffs der Stabilitaet des Problems der
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Kibernetika, Kiev 1970, No.4, 139-140, 1970.
F. Archetti.
Evaluation of random gradient techniques for unconstrained
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Calcolo 12, 83-94, 1975.
F. Archetti, G. Di Pillo, and M. Lucertini, editors.
Stochastic programming, volume 76 of Lecture Notes in
Control and Information Sciences, Berlin, 1986. Springer-Verlag.
Papers from the conference held in Gargnano, September 15-21, 1983.
F. Archetti and F. Frontini.
The application of a global optimization method to some
technological problems.
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F. Archetti, A. Gaivoronski, and A. Sciomachen.
Sensitivity analysis and optimization of stochastic Petri nets.
Discrete Event Dyn. Syst. 3, No.1, 5-37, 1993.
F. Archetti and F. Schoen.
A survey on the global optimization problem: General theory and
computational approaches.
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Gorguano/Italy 1982, Ann. Oper. Res. 1, 87-110, 1984.
Francesco Archetti.
Analysis of stochastic strategies for the numerical solution of the
global optimization problem.
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Gargnano/Italy 1979, 275-295, 1980.
Francesco Archetti.
A probabilistic algorithm for global optimization problems with a
dimensionality reduction technique.
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Francesco Archetti and Bruno Betrò.
Stochastic models and optimization.
Boll. Un. Mat. Ital. A (5), 17(2):295-301, 1980.
T. W. Archibald, C. S. Buchanan, K. I. M. McKinnon, and L. C. Thomas.
Nested Benders decomposition and dynamic programming for reservoir
optimisation.
Journal of the Operational Research Society, 50(5):468-479,
1999.
T. W. Archibald, C. S. Buchanan, L. C. Thomas, and K. I. M. McKinnon.
Controlling multi-reservoir systems.
European Journal of Operational Research, 129(3):619-626,
2001.
R. Ardanuy and A. Alcalá.
Weak infinitesimal operators and stochastic differential games.
Stochastica, 13(1):5-12, 1992.
K. A. Ariyawansa, C. Cacho, and A. J. Felt.
A family of stochastic programming test problems based on a model for
tactical manpower planning.
J. Math. Model. Algorithms, 4(4):369-390, 2005.
K. A. Ariyawansa and Andrew J. Felt.
On a new collection of stochastic linear programming test problems.
INFORMS J. Comput., 16(3):291-299, 2004.
K. A. Ariyawansa and Yuntao Zhu.
Stochastic semidefinite programming: a new paradigm for stochastic
optimization.
4OR, 4(3):239-253, 2006.
K. A. Ariyawansa and Yuntao Zhu.
A class of volumetric barrier decomposition algorithms for stochastic
quadratic programming.
Appl. Math. Comput., 186(2):1683-1693, 2007.
K.A. Ariyawansa.
Performance of a benchmark implementation of the Van Slyke and Wets
algorithm for stochastic programs on the alliant FX/8.
In Dongarra, Jack (ed.) et al., Proceedings of the fifth SIAM
conference on parallel processing for scientific computing, held in Houston,
TX, USA, March 25-27, 1991. Philadelphia, PA: SIAM, (ISBN 0-89871-303-X/pbk).
186- 192, 1992.
Vadim I. Arkin.
Stochastic optimization approach to dynamic problems with jump
changing structure.
In Stochastic programming methods and technical applications
(Neubiberg/Munich, 1996), pages 104-110. Springer, Berlin, 1998.
V.I. Arkin.
Economic dynamics and discretely varying technology. Probabilistic
approach.
In Probability and mathematical economics, Moskva, 3-30,
1988.
V.I. Arkin and I.V. Evstigneev.
Probabilistic models of control and economic dynamics.
(Veroyatnostnye modeli upravleniya i ehkonomicheskoj dinamiki).
Moskva: "Nauka"., 1979.
V.I. Arkin, A. Shiraev, and R. Wets, editors.
Stochastic Optimization. Proceedings of the International
Conference, Kiev 1984.
Springer, Berlin, 1986.
LN in Control and Information Sciences 81.
V.I. Arkin and S.A. Smolyak.
On the structure of optimality criteria in stochastic optimization
models.
In Stochastic optimization, Proc. Int. Conf., Kiev/USSR 1984,
Lect. Notes Control Inf. Sci. 81, 275-286, 1986.
Ronald D. Armstrong and Joseph L. Balintfy.
A chance constrained multiple choice programming algorithm with
applications.
In Stochastic programming (Proc. Internat. Conf., Univ. Oxford,
Oxford, 1974), pages 301-325. Academic Press, London, 1980.
Klaus-Peter Arnold.
Stochastische Transportprobleme.
Verlag Dr. Kovac, Hamburg, 1987.
H. Arsham.
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Tactical manpower planning via programming under uncertainty.
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Entscheidungsprobleme mit linearem Aktionen- und Ergebnisraum.
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Methods Oper. Res. 36, 223-234, 1980.
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Stochastic dominance and the construction of descent directions in
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Stochastische Dominanz und Konstruktion von Abstiegsrichtungen in
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Ueber die Berechnung von Abstiegsrichtungen in Stochastischen
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Minimizing noisy objective functions by random search methods.
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On the construction of descent directions in stochastic programs
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Z. Angew. Math. Mech., 64(5):336-338, 1984.
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Computation of descent directions in stochastic optimization problems
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Z. Angew. Math. Mech., 67(5):T408-T410, 1987.
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Descent stochastic quasigradient methods.
In Numerical techniques for stochastic optimization, volume 10
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Optimal semistochastic approximation.
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In Stochastic versus fuzzy approaches to multiobjective
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Stochastic optimization methods in structural mechanics.
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Bericht über die Wissenschaftliche Jahrestagung der GAMM
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Stochastic programming: numerical solution techniques by
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Semi-stochastic approximation by the response surface methodology
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Optimization, 25(2-3):209-230, 1992.
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Stochastic optimization in structural design.
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Bericht über die Wissenschaftliche Jahrestagung der GAMM (Kraków,
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Stochastic Optimization. Numerical Methods and Technical
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Satisficing techniques in stochastic linear programming.
Optimization, 31(4):359-384, 1994.
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Differentiation formulas for probability functions: the
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Path planning for robots under stochastic uncertainty.
Optimization, 45(1-4):163-195, 1999.
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Stochastic programming methods in adaptive optimal trajectory
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On the convergence rate of semistochastic approximation procedures.
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Computation of descent directions and efficient points in stochastic
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Optimale Portefeuilles mit stabil verteilten Renditen.
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An algorithm for the approximate solution of the maximization problem
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Konvexitätsaussagen zum linearen stochastischen
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Approximationen der Entscheidungsprobleme mit linearer
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Approximations to gradients in stochastic programming.
Bull. Inst. Internat. Statist., 46(4):137-140 (1976), 1975.
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Convex approximation of stochastic optimization problems.
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Approximations to stochastic optimization problems.
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Stochastische Dominanz und stochastische lineare Programme.
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On stochastic dominance relations in stochastic programming.
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Stochastic linear programs with random data having stable
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Approximationen stochastischer Optimierungsprobleme,
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On solutions of stochastic programming problems by descent procedures
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In Third Symposium on Operations Research (Univ. Mannheim,
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Approximations to stochastic optimization problems.
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On accelerations of the convergence in random search methods.
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Solving stochastic linear programs by semistochastic approximation
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On accelerations of stochastic gradient methods by using more exact
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Optimally controlled semi-stochastic approximation procedures.
In Ökonomie und Mathematik, pages 216-230, Berlin, 1987.
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Descent directions and efficient solutions in discretely
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Springer-Verlag, Berlin, 1988.
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Stochastic optimization methods in engineering.
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Structural reliability and stochastic structural optimization.
Physica-Verlag, Heidelberg, 1997.
Math. Methods Oper. Res. 46 (1997), no. 3.
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Adaptive optimal stochastic trajectory planning and control
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Numerical methods for stochastic optimization and real-time
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Stochastic optimization methods in robust adaptive control of robots.
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Robust optimal design: a stochastic optimization problem.
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Stochastic Optimization Methods.
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