Bibliography

1

K. A. Ariyawansa and A. J. Felt.
On a new collection of stochastic linear programming test problems.
Technical Report 01-04, Pure and Applied Mathematics, Washington State University, Pullman, WA 99164-3113, May 2001.
http://www.optimization-online.org/DB_HTML/2001/05/334.html

2

J. R. Birge.
Stochastic programming computation and applications.
INFORMS Journal on Computing, 9:111-133, 1997.
http://joc.pubs.informs.org/BackIssuesVol009TOC.html

3

J. R. Birge, C. J. Donohue, D. F. Holmes, and O. G. Svintsitski.
A parallel implementation of the nested decomposition algorithm for multistage stochastic linear programs.
Mathematical Programming, 75:327-352, 1996.
local copy

4

C. C. Car and R. Schultz.
Dual decomposition in stochastic integer programming.
Operations Research Letters, 24(1-2):37-45, 1999.
local copy
To be presented by Xiaoyun Ji.

5

C. C. Car and J. Tind.
L-shaped decomposition of two-stage stochastic programs with integer recourse.
Mathematical Programming, 83:451-464, 1998.
local copy

6

K. Cormican, D. Morton, and R. Wood.
Stochastic network interdiction.
Operations Research, 46(2):184-197, 1998.
available via the library's list of e-journals

7

S. J. Drijver, W. K. Klein Haneveld, and M. H. van der Vleck.
Asset liability management modeling using multistage mixed-integer stochastic programming.
Technical report, SOM, University of Groningen, The Netherlands, 2000.
http://www.ub.rug.nl/eldoc/som/a/00A52/
To be presented by Carol McGeoch.

8

S.-E. Fleten, K. Høyland, and S. W. Wallace.
The performance of stochastic dynamic and fixed mix portfolio models.
European Journal of Operational Research, 140(1):37-49, 2002.
available via the library's list of e-journals
or http://home.himolde.no/~wallace/reports.htm
To be presented by Lepeng Li.

9

E. Fragniere, J. Gondzio, and J.-P. Vial.
Building and solving large-scale stochastic programs on an affordable distributed computing system.
Annals of Operations Research, 99:167-187, 2000.
http://ecolu-info.unige.ch/~logilab/reports/million2.pdf
or http://www.maths.ed.ac.uk/~gondzio/reports/Welcome.html

10

G. A. Godfrey and W. B. Powell.
An adaptive, distribution-free approximation method for the newsvendor problem with censored demands, with applications to inventory and distribution problems.
Management Science, 47(8):1101-1112, 2001.
http://www.castlelab.princeton.edu/Papers/2stage.pdf
also available via the library's list of e-journals
To be presented by Yuh-Fen Wong.

11

J. Gondzio and R. Kouwenberg.
High-performance computing for asset-liability management.
Operations Research, 49(6):879-891, 2001.
http://www.maths.ed.ac.uk/~gondzio/reports/wrecord.pdf
also available via the library's list of e-journals
or http://www.maths.ed.ac.uk/~gondzio/reports/Welcome.html

12

N. Gulpinar, B. Rustem, and R. Settergren.
Multistage stochastic programming in computational finance.
In E. J. Kontoghiorghes, B. Rustem, and S. Siokos, editors, Computational Methods in Decision-Making, Economics and Finance, volume 74 of Applied Optimization, chapter 3. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002.
http://www.doc.ic.ac.uk/~reuben/jobs/stochastic.ps
To be presented by Xiang Zhi.

13

K. Haugen and S. W. Wallace.
Market mechanisms and stochastic programming.
Technical report, Molde University College, Norway, December 2001.
http://home.himolde.no/~wallace/market.ps
or http://home.himolde.no/~wallace/reports.htm
To be presented by Kris Farwell.

14

J. L. Higle.
Variance reduction and objective function evaluation in stochastic linear programs.
INFORMS Journal on Computing, 10:236-247, 1998.
local copy, pages 236 to 246 and page 247
To be presented by Daryn Ramsden.

15

J. Linderoth and S. Wright.
Decomposition algorithms for stochastic programming on a computational grid.
Technical Report Preprint ANL/MCS, Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439, April 2001.
http://www.optimization-online.org/DB_HTML/2001/04/315.html
or http://www.cs.wisc.edu/~swright/papers

16

J. T. Linderoth, A. Shapiro, and S. J. Wright.
The empirical behavior of sampling methods for stochastic programming.
Technical Report Optimization Technical Report 02-01, Computer Sciences Department, University of Wisconsin, Madison, January 2002. Revised October 2002.
http://w ww.optimization-online.org/DB_HTML/2002/01/424.html
or http://www.cs.wisc.edu/~swright/papers

17

W. K. Mak, D. P. Morton, and R. K. Wood.
Monte carlo bounding techniques for determining solution quality in stochastic programs.
Operations Research Letters, 24:47-56, 1999.
local copy

18

J. M. Mulvey and K. Simsek.
Rebalancing strategies for long-term investors.
In E. J. Kontoghiorghes, B. Rustem, and S. Siokos, editors, Computational Methods in Decision-Making, Economics and Finance, volume 74 of Applied Optimization, chapter 6. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2002.
http://www.hermes.ucy.ac.cy/publications/conference_may_2000/Mulvey.pdf
To be presented by Jim Burnes.

19

J. M. Mulvey, R. J. Vanderbei, and S. J. Zenios.
Robust optimization of large-scale systems.
Operations Research, 43:264-281, 1995.
available via the library's list of e-journals
To be presented by Rusty Lee.

20

R. Rush, J. M. Mulvey, J. E. Mitchell, and T. R. Willemain.
Stratified filtered sampling in stochastic optimization.
Journal of Applied Mathematics and Decision Sciences, 4(1):17-38, 2000.
http://www.rpi.edu/~mitchj/papers/filtered.html

21

S. Sen and J. L. Higle.
An introductory tutorial on stochastic linear programming models.
Interfaces, 29(2):33-61, 1999.
available via the library's list of e-journals
To be presented by Ali Yasar.

22

S. Seshadri, A. Khanna, F. Harche, and R. Wyle.
A method for strategic asset-liability management with an application to the Federal Home Loan Bank of New York.
Operations Research, 47(3):345-360, 1999.
available via the library's list of e-journals

23

S. Takriti and S. Ahmed.
On robust optimization of two-stage systems.
Technical report, Mathematical Sciences Department, T. J. Watson Research Center, IBM, Yorktown Heights, NY, February 2001.
http://www.optimization-online.org/DB_HTML/2001/02/283.html
To be presented by Shawne Campbell.

24

S. Takriti and J. R. Birge.
Lagrangian solution techniques and bounds for loosely coupled mixed-integer stochastic programs.
Operations Research, 48(1):91-98, 2000.
available via the library's list of e-journals

25

B. Verweij, S. Ahmed, A. Kleywegt, G. L. Nemhauser, and A. Shapiro.
The sample average approximation method applied to stochastic routing problems: A computational study.
Technical report, The Logistics Institute, Georgia Institute of Technology, Atlanta, GA, August 2001.
http://www.optimization-online.org/DB_HTML/2001/09/369.html

26

R. J.-B. Wets.
Challenges in stochastic programming.
Mathematical Programming, 75:115-135, 1996.
local copy

27

Y. Zhao and W. T. Ziemba.
A stochastic programming model using an endogenously determined worst case risk measure for dynamic asset allocation.
Mathematical Programming, 89(2):293-309, 2001.
available via the library's list of e-journals

28

J. M. Mulvey.
Introduction to financial optimization: Mathematical Programming special issue.
Mathematical Programming, 89(2):205-216, 2001.
available via the library's list of e-journals

29

A. Consiglio and S. Zenios.
Designing portfolios of financial products via integrated simulation and optimization models.
Operations Research, 47(2):195-208, 1999.
available via the library's list of e-journals

30

O. Bahn, O. Du Merle, J. L. Goffin and J. P. Vial.
A cutting plane method from analytic centers for stochastic programming.
Mathematical Programming, 69(1):45-73, 1995.
too old to be available online