1. Ho, Y.C., Sreenivas, R., Vakili, P.,"Ordinal Optimization of Discrete Event
   Dynamic Systems", J. of DEDS 2(2), 61-88, (1992).

This is the first paper on ordinal optimization. It introduces
the idea and demonstrates via a series of simulation experiments that considerable
saving in computation is possible if one is willing to ask a softer question,
namely, "not is this the best but is this good enough"?
 

2. Patsis, N., Chen, C.H., & Larson, M.,"Parallel Simulation of DEDS",
   Proceeding of Optimization Days , Montreal, Canada (1993) to appear
   in IEEE Trans. on Control Technology (1996)

This paper won the runner up award on the 1992 MasPar Challenge
for Massively Parallel Computation as having the highest speedup and scalability
 

3. Deng, M., Ho, Y.C., and Hu, J.Q. "Effect of Correlated Estimation Error
   in Ordinal Optimization", Proceedings of the Winter Simulation Conference
   , December (1992), pp 466-475.

This paper studies the effect of correlated estimation errors
(vs. i.i.d. errors) in ordinal optimization and concludes that the effects
of correlation is minimal and generally only help rather than hinder the
conclusion.
 

4. Y. C. Ho, "A New Paradigm for Stochastic Optimization and Parallel Simulation"
   Proc. of 1993 DES Workshop in IMA/U.Minn Lecture Notes Series, Springer-Verlag,
   (1994) Prsented at the IMA workshop 5/23/93 in Minneapolis and the ORSA/TIMS/INRIA
   Conference on Applied Probability in Paris 6/18/93

This paper outlines the vision of using ordinal optimization
and massively parallel simulation concurrently to improve simulation efficiency
by orders of magnitude.
 

5. Y. C. Ho,"Heuristics, Rules of Thumb, and the 80/20 Proposition" to appear
   IEEE Trans. on Automatic Control , Vol 39, #5, 1025-1027, May 1994

This is probable the quickest introduction to the idea of ordinal
optimization.
 

6. Y. C. Ho and M. Larson, "Ordinal Optimization and Rare Event Probability
   Simulation" J. Discrete Event Dynamic Systems, Vol 5, #2-3, 1995

This paper shows the idea of a surrogate problem in ordinal
optimization and ordinal equivalence. Rare event probabilities can be compared
using not so rare event probabilities resulting in massive computational
saving.
 

7. Wieseltheir, J.E., Barnhart, C.M., and Ephremides, A., "Ordinal Optimization
   of Admission control in Wireless Multihop Voice/Data Nework via Standard
   Clock Simulation", J.DEDS, Vol.5, #2-3, 1995.

This is the first application of OO by an outside group.
 

8. A. Ganz and X. Wang, "Efficient algorithm for virtual topology design in
   multihop lightwave networks," IEEE/ACM Transactions on Networking,
   vol. 2, June 1994.

9. Xie, Xiaohan , "An Ordinal Optimization Approach to a Token Partition Problem
   for Stochastic Timed Event Graphs" m/s INRIA, Technopole Metz 2000, 57070
   Metz, France

Two more applications: Using parallel simulation, OO, and Chen's
optimal budget to solve the choice of initial marking.
 

10. Dai, Li-Yi, "Convergence Properties of Ordinal Comparison in the Simulation
    of Discrete Event Dynamic Systems", J. of Opt. Th. & App., Vol.91,
    No.2. pp.363-388, 1996.

11. Xie, Xiaolan "Dynamics and Convergence Rate of Ordinal Comparison of Stochastic
    Discrete Event Systems", IEEE Trans. on Auto. Control, Vol.42, No.4, 
    pp.586-590, April 1997.

First Proofs of the fact "order converges faster than value".

12. Lau, T.W.E. and Ho, Y.C., "Universal Alignment Probabilities and Subset
    Selection for Ordinal Optimization", JOTA , Vol.39, #3 June 1997, 455-490.

13. Deng, M. And Ho, Y.C., "An Ordinal Optimization Approach to Optimal Control Problems",
    AUTOMATICA, Vol.35, pp. 331-338, 1999.

14. Lee, L.H, Lau, T.W.E., Ho, Y.C., "Explanation of Goal Softening in Ordinal
    Optimization", IEEE Trans. on Auto. Control, Vol.44, #1, pp.94-99, 1999.

    Recent foundational works on OO

15. Z. B. Tang and Ho, Y.C., "Modification of Adaptive Partitioned Random Search",
    Proc. 1995 Conference on Decision and Control

16. L. Dai and C.-H. Chen, "Rates of convergence of ordinal comparison for
    dependent discrete event dynamic systems", J. Optimization Theory and Applications,
    Vol. 94, No. 1, July, 1997

17. Y.C. Ho, "On the Numerical Solution of Stochastic Optimization Problems",
    IEEE Tran. on Automatic Control, 42, #5, 1997.

18. Yang, M.S., Lee, L.H., and Ho, Y.C., "On Stochastic Optimization and Its
    Applications to Manufacturing" Proc. of AMS Conference on Stochastic Problems
    in Manufacturing, Springer-Verlag Lecture Notes in Applied Mathematics 
    Vol. 33, 317-331, 1997

    Successful applications of OO to two real life manufacturing problems
    involving turbine blade and tailoredclothing manufacturing.

19. Ho, Y.C., "Explanation of ordinal optimization: Soft computing for hard problems", 
    Information Sciences, Vol.113, No.3-4, pp.169-192, Feb, 1999.

20. Lee, J.T., Lau, E., and Ho, Y.C., "The Witsenhausen Counterexample: A Hierarchical
    Search Approach for Nonconvex Optimization Problems", IEEE Transactions on Automatic
    Control, Vol.46, No.3, pp.382-397, March 2001.

21. Li, D., Lee, L.H., and Ho, Y.C., "Constraint ordinal optimization", 
    Information Sciences, Vol.148, pp.201-220, 2002.

Related Literature in Statistics

1. Gibbons, J.D., Olkin, I., and Sobel, M.,Selecting and Ordering of Populations, Wiley, (1977).

2. Santner, T.J., and Tamhane, A.C.,Design of Experiments: Ranking and Selection, M. Dekker, (1984).

3. Bechhofer, R.E.,"A single Sample Multiple Choice Procedure for Ranking Means of Normal Population with known Variance", Annals of Mathematical Statistics 25, 16-39, (1954).

4. M. Sobel "On Selecting a Subset Containing at Least One of the t Best Population" in Multivariate Analysis - II (P.R. Krishnaiah, Ed.) Academic Press, 1969, 515-540

5. Goldman, D., and Nelson, B.L., "Ranking, Selection, and Multiple Comparisons in Computer Simulation" 1994 Winter Simulation Conferecne Prioceedings

Other Related Literature

1. Serhat Yesilyurt & Anthony Patera, "Surrogate for Numerical Simulation; Optimization of Eddy-Promotor Heat Exchanger" Submitted to Computer Method in Applied Mechanics and Engineering, July 1993

2. Serhat Yesilyurt, C. Ghaddar, M. Cruz, A. T. Patera " Bayesian -Validaterd Surrogate for Noisy Computer Simulation: Application to Randon Media" Submitted to SIAM Journal on Scientific Computing, Nov. 1993

3. Glasserman, P. and Vakili, P. "Correlation of Uniformized Markov Chains Simulated in Parallel", Proceedings of the Winter Simulation Conference , December (1992), pp 412-419

4. Glasserman, P. and Yao, David "Some Guidelines and Guarantees for Common Random Numbers", Management Science, (1994)

Related Literature on Doing a Set of Parallel Simulations Efficiently

1. Vakili, P.,"A Standard Clock Technique for Efficient Simulation", Operations Research Letters 10, 445-452, (1991).

2. Vakili, P. Mollamustafaoglu, L., Ho, Y.C.,"Massively Parallel Simulation of a Class of Discrete Event Systems", Proc. of the 4th IEEE Massively Parallel Computation Conference , (1992).

3. Vakili, P., "Massively Parallel and Distributed Simulation of a class of Discrete Event Systems : a different perspective", ACM Transactions on Modeling and Computer Simulation , July 1993.

4. C.H. Chen and Y. C. Ho, "Extensions of the Standard Clock Method for Discrete Event Simulation", to appear IEEE Trans. on Control Technology,1995

5. Hu, J.Q., "Parallel Simulation via Event Synchronization", to appear J. of Discrete Event Dynamic Systems, Vol.5, #2-3, 1995.

6. Cassandras, C.G., Discrete Event Systems: Modeling and Performance Analysis, Irwin Publ., 1993.

7. Chen, C-H, and Ho, Y.C. "An Approximation Approach of the Standard Clock Method for General Discrete Event Simulation" , IEEE Trans. on Control System Technology, v.3, #3, Sept. 1995 309-317