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To recognize outstanding contributions to the simulation literature, the INFORMS Simulation Society annually sponsors an Outstanding Simulation Publication Award. Anyone is eligible to win the Award. Journal articles, proceedings articles, books, and monographs are eligible contribitions. Past recipients of this award are:
1981 -- Schruben, Lee W. 1980. A coverage function for interval estimators of simulation response. Management Science 26 (1): 18--27. 1982 -- Lavenberg, Stephen S., and Peter D. Welch. 1981. A perspective on the use of control variables to increase the efficiency of Monte Carlo simulations. Management Science 27 (3): 322--335. 1983 (tie) -- Meketon, Marc S., and Philip Heidelberger. 1982. A renewal theoretic approach to bias reduction in regenerative simulations. Management Science 28 (2): 173--181. 1983 (tie) -- Law, Averill M., and W. David Kelton. 1982. Confidence interval procedures for steady-state simulations, II: A survey of sequential procedures. Management Science 28 (5): 550--562. 1984 -- Not given. 1985 -- Wilson, James R., and A. Alan B. Pritsker. 1984. Experimental evaluation of variance reduction techniques for queueing simulation using generalized concomitant variables. Management Science 30 (12): 1459--1472. 1986-- Not given 1987 -- Schruben, Lee W. 1983. Confidence interval estimation using standardized time series. Operations Research 31 (6): 1090--1108. 1988 -- Zeigler, Bernard P. 1984. Multifacetted modelling and discrete event simulation. London: Academic Press. 1989 -- Devroye, Luc. 1986. Non-uniform random variate generation. New York: Springer-Verlag. 1990 -- Heidelberger, Philip , Xi-Ren Cao, Michael A. Zazanis, and Rajan Suri. 1988. Convergence properties of infinitesimal perturbation analysis estimates. Management Science 34 (11): 1281--1302. 1991 -- Whitt, Ward. 1989. Planning queueing simulations. Management Science 35 (11): 1341--1366. 1992 -- Glasserman, Paul. 1991. Gradient estimation via perturbation analysis. Boston: Kluwer Academic Publishers. 1993 -- Fox, Bennett L., and Peter W. Glynn. 1990. Discrete-time conversion for simulating finite-horizon Markov processes. SIAM Journal on Applied Mathematics 50 (5): 1457--1473. 1994 -- Fujimoto, Richard M. 1990. Parallel discrete event simulation. Communications of the ACM 33 (10): 30--53. 1995 -- Niederreiter, Harald. 1992. Random number generation and quasi--Monte Carlo methods. Philadelphia: Society for Industrial and Applied Mathematics. 1996 -- Shahabuddin, Perwez. 1994. Importance sampling for the simulation of highly reliable Markovian systems. Management Science 40 (3): 333--352. 1997 -- Fishman, George. 1996. Monte Carlo: Concepts, Algorithms, and Applications. New York: Springer-Verlag. 1998 -- Fu, Michael, and Jian-Qiang Hu. 1997. Conditional Monte Carlo: Gradient Estimation and Optimization Applications. Boston: Kluwer Academic Press. 1999 -- L'Ecuyer, Pierre. 1996. Combined Multiple Recursive Random Number Generators. Operations Research, 44 (5), 816--822. Maximally Equidistributed Combined Tausworthe Generators. Mathematics of Computation, 65 (213), 203--213. 2000 -- Propp, James and David Wilson. 1996. Exact Sampling with Coupled Markov Chains and Applications to Statistical Mechanics. Random Structures and Algorithms, volume 9 , 223--252. 1998. Coupling from the past: a user's guide. Microsurveys in Discrete Probability, Volume 41 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 181--192. American Mathematical Society. 2001 -- Law, Averill M., and W. David Kelton. 1999. Simulation Modeling and Analysis, 3rd edition, New York: McGraw-Hill 2002 -- Asmussen, Soren, Klemens Binswanger, and Bjarne Hojgaard. 2000. Rare events simulation for heavy-tailed distributions. Bernoulli, 6 (2): 303--322 2003 -- Haas, Peter. 2002. Stochastic Petri Nets: Modelling, Stability, Simulation, New York: Springer 2004-- Not given 2005 -- Glasserman, Paul. 2003. Monte Carlo Methods in Financial Engineering, New York: Springer 2006 -- Boesel, Justin, Barry Nelson and Seong-hee Kim. 2003. Using Ranking and Selection to "Clean Up" After Simulation Optimization. Operations Research 51(5): 814--825 2007 --
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