Table of Contents

• Why simulation worksA. Alan B. Pritsker. 1-9 [doi]
• Simulation for decision making: an introductionArne Thesen, Laurel E. Travis. 9-18 [doi]
• Parallel discrete event simulationRichard M. Fujimoto. 19-28 [doi]
• Selecting simulation software for manufacturing applicationsAverill M. Law, S. W. Haider. 29-32 [doi]
• Tutorial: artificial intelligence and simulationJeff Rothenberg. 33-39 [doi]
• A tutorial on uniform variate generationPierre L Ecuyer. 40-49 [doi]
• Graphical methods for the design and analysis of simulation experimentsRussell R. Barton, Lee W. Schruben. 51-61 [doi]
• How to assess the acceptability and credibility of simulation resultsOsman Balci. 62-71 [doi]
• The simulation process: avoiding the problems and pitfallsRandall P. Sadowski. 72-79 [doi]
• Rapid modeling: how it assists manufacturing competitivenessRajan Suri. 80-83 [doi]
• Hierarchical, modular modelling in DEVS-schemeBernard P. Zeigler, J. H. Hu, Jerzy W. Rozenblit. 84-89 [doi]
• Optimization of stochastic systems via simulationPeter W. Glynn. 90-105 [doi]
• Simulation run length planningWard Whitt. 106-112 [doi]
• Perspectives on simulation using GPSSThomas J. Schriber. 115-128 [doi]
• Introduction to SIMANDavid T. Sturrock, Claude Dennis Pegden. 129-139 [doi]
• A tutorial introduction to object-oriented simulation and SIM+ +Greg Lomow, Dirk Baezner. 140-146 [doi]
• Computer animation with CINEMAJacob P. Poorte, Deborah A. Davis. 147-154 [doi]
• A general purpose animatorDaniel T. Brunner, James O. Henriksen. 155-163 [doi]
• Productivity tools in simulation: SIMSCRIPT 11.5 and SIMGRAPHICSOtis F. Bryan Jr.. 164-171 [doi]
• MODSIM II-an object oriented simulation language for sequential and parallel processorsOtis F. Bryan Jr.. 172-177 [doi]
• Introduction to SLAM II and SLAMSYSTEMJean J. O Reilly, Kristen C. Nordlund. 178-183 [doi]
• The GPSS/PC student versionS. W. Cox. 185-191 [doi]
• A tutorial on SEE WHY and WITNESSAndrew R. Gilman, Claire Billingham. 192-200 [doi]
• Introduction to SIMFACTORY 11.5M. C. Rohbough. 201-204 [doi]
• NETWORK 11.5 Tutorial: network modeling - without programmingWilliam J. Garrison. 205-214 [doi]
• Communication network analysis with COMNET 11.5Robb Mills. 215-221 [doi]
• Knowledge-based modeling and simulation componentsJeff Kaminski, Cindy Cosic, Gary Strohm, Joyce Kepner, Jim Bycura. 222-231 [doi]
• The SimKit system: knowledge-based simulation and modeling tools in KEEMarilyn Stelzner, Jack Dynis, Fred Cummins. 232-234 [doi]
• AutoMod II: the system builderM. B. Thompson. 235-242 [doi]
• The MAST simulation environmentJohn E. Lenz. 243-248 [doi]
• Extended features of GPSS/HRobert C. Crain, Daniel T. Brunner. 249-253 [doi]
• Simulation with MIC-SIM and MIC-SIM VIEWDavid E. Strack. 254-256 [doi]
• Estimating system availability and reliabilityAmbuj Goyal. 257-265 [doi]
• Stochastic petri net simulationGianfranco Balbo, Giovanni Chiola. 266-276 [doi]
• Tutorial: scheduling manufacturing systems with FACTORFloyd H. Grant. 277-280 [doi]
• SIMPLE_1: the language & modeling environmentPhilip Cobbin. 281-290 [doi]
• Simulation modeling and analysis with INSIGHT: a tutorialStephen D. Roberts, Mary Ann Flanigan Wagner. 291-300 [doi]
• DISC++: A C++ based library for object oriented simulationEric L. Blair, Sathyakumar Selvaraj. 301-305 [doi]
• Modeling input processes with Johnson distributionsDavid J. DeBrota, Robert S. Dittus, James J. Swain, Stephen D. Roberts, James R. Wilson. 308-318 [doi]
• Pre-and post-processing for data efficiency in large-scale computer simulationsTurkan K. Gardenier. 319-324 [doi]
• Statistical issues in a general-purpose simulation modeling languageStephen D. Roberts, Robert W. Klein. 325-333 [doi]
• A graphical test bed (SIMTBED) for analyzing and reporting the results of a statistical experimentPeter A. W. Lewis. 334-343 [doi]
• Analysis of simulation data using sandieArne Thesen. 344-349 [doi]
• Teaching simulation with MOR/DSGuy L. Curry, Bryan L. Deuermeyer, Richard M. Feldman. 350-359 [doi]
• Teaching simulation with Pascal_SIMRobert M. O Keefe, Ruth M. Davies. 360-364 [doi]
• Simulation sensitivity analysis using frequency domain experimentsDouglas J. Morrice, Lee W. Schruben. 367-373 [doi]
• Likelihood ratio derviative estimators for stochastic systemsPeter W. Glynn. 374-380 [doi]
• Derivative estimates from discontinuous realizations: smoothing techniquesPaul Glasserman, Wei-Bo Gong. 381-389 [doi]
• Optimization of an automated manufacturing system simulation model using simulated annealingE. M. Manz, Jorge Haddock, John Mittenthal. 390-395 [doi]
• Using computer simulation to optimize flexible manufacturing systems designU. Nandkelyar, D. P. Christy. 396-405 [doi]
• Oscillation amplitude considerations in frequency domain experimentsSheldon H. Jacobson. 406-410 [doi]
• Experimental design issues for large scale simulation modelsRussell R. Barton. 411-418 [doi]
• Implementation of quasi-random generators and their use in discrete event simulationT. R. Davenport, R. C. H. Cheng. 419-427 [doi]
• A flexible method for estimating inverse distribution functions in simulation experimentsAthanassios N. Avramidis, James R. Wilson. 428-436 [doi]
• Response surface analysis of stochastic network performanceThomas G. Bailey, Kenneth W. Bauer Jr., A. B. Marsh. 437-443 [doi]
• Optimization using common random numbers, control variates and multiple comparisons with the bestWei-Ning Yang. 444-449 [doi]
• Variance reduction of quantile estimates via nonlinear controlPeter A. W. Lewis, Richard L. Ressler. 450-454 [doi]
• Augmenting linear control variates using transformationsJames J. Swain. 455-458 [doi]
• Random number generation on parallel processorsMasanori Fushimi. 459-461 [doi]
• Using linear congruential generators for parallel random number generationMark J. Durst. 462-466 [doi]
• About polynomial-time unpredictable generatorsPierre L Ecuyer, René Proulx. 467-476 [doi]
• Mathematical aspects of various methods for sampling from classical distributionsUlrich Dieter. 477-483 [doi]
• Ratio of uniforms as a convenient method for sampling from classical discrete distributionsErnst Stadlober. 484-489 [doi]
• Inverse-transformation algorithms for some common stochastic processesBruce W. Schmeiser, Wheyming Tina Song. 490-496 [doi]
• Monte Carlo simulation of complex system mission reliabilityE. E. Lewis, F. Boehm, C. Kirsch, B. P. Kelkhoff. 497-504 [doi]
• Large deviations theory techniques in Monte Carlo simulationJohn S. Sadowsky, James A. Bucklew. 505-513 [doi]
• Quick simulation of rare events in networksRoman D. Fresnedo. 514-523 [doi]
• Multivariate inferences for regenerative simulations to a specified precision levelDer-Fa Robert Chen. 524-533 [doi]
• A principal components model of simulation structureDavid Alan Grier. 534-537 [doi]
• Correlation-induction techniques for fitting second-order metamodels in simulation experimentsJeffrey D. Tew. 538-546 [doi]
• Testing, understanding, and validating complex simulation modelsJerry Banks. 549-551 [doi]
• Verification and validation: a consultant s perspectiveJohn S. Carson II. 552-558 [doi]
• Guidelines for selecting and using simulation model verification techniquesRichard B. Whitner, Osman Balci. 559-568 [doi]
• Simulating hybrid connectionist architecturesTrent E. Lange, Jack B. Hodges, Maria E. Fuenmayor, Leonid V. Belyaev. 569-578 [doi]
• Simulation system for the control of manufacturing linesJ. Beaudoin, G. Feldmann, Pierre Massotte. 579-583 [doi]
• The role of knowledge management in hierarchical model developmentYueh-Min Huang, Jerzy W. Rozenblit, Jhyfang Hu. 584-592 [doi]
• Object oriented toolkits for simulation program generatorsOnur M. Ülgen, Timothy Thomasma, Youyi Mao. 593-600 [doi]
• Olympus: an interactive simulation systemGary J. Nutt, Adam Beguelin, Isabelle M. Demeure, R. Stephen Elliot, Jeffrey D. McWhirter. 601-611 [doi]
• Animating simulations in RESQMEA. Aggarwal, Kurtiss J. Gordon, James F. Kurose, Robert F. Gordon, Edward A. MacNair. 612-620 [doi]
• Distributed simulation using hierarchical rollbackR. L. Gimarco. 621-629 [doi]
• Rollback sometimes works...if filteredBoris D. Lubachevsky, Adam Shwartz, Alan Weiss. 630-639 [doi]
• Adaptive distribution of model components via congestion measuresMurali S. Shanker, W. David Kelton, Rema Padman. 640-647 [doi]
• Alternative modeling perspectives: finding the creative sparkJames O. Henriksen. 648-652 [doi]
• Developing analytic models based on simulation resultsA. A. B. Prisker. 653-660 [doi]
• A common programming structure for Bryant-Chandy-Misra, time-warp, and sequential simulatorsM. Abrams. 661-670 [doi]
• Comparative analyses of parallel simulation protocolsPaul F. Reynolds Jr., Christopher F. Weight, J. Robert Fidler. 671-679 [doi]
• Efficient aggregation of multiple PLs in distributed memory parallel simulationsDavid M. Nicol, Chris C. Michael, Patrick Inouye. 680-685 [doi]
• How technology limits simulation methodology (panel)Claude Dennis Pegden. 686-691 [doi]
• A logic for simulating discontinous systemsSanjai Narain, Jeff Rothenberg. 692-701 [doi]
• Neural network models in simulation: a comparison with traditional modeling approachesPaul A. Fishwick. 702-709 [doi]
• A comparison of selected conceptual frameworks for simulation modelingE. Joseph Derrick, Osman Balci, Richard E. Nance. 711-718 [doi]
• Marked event method in discrete event simulationShu Li. 719-728 [doi]
• On analyzing events to estimate the possible speedup of parallel discrete event simulationTapas K. Som, Bruce A. Cota, Robert G. Sargent. 729-737 [doi]
• Simulation graph duality: a world view transformation for simple queueing modelsLee W. Schruben, Enver Yücesan. 738-745 [doi]
• Parallel simulation: practice: contrasting distributed simulation with parallel replication: a case study of a queuing simulation on a network of transputersR. Rajagopal, John Craig Comfort. 746-755 [doi]
• Experience with concurrent simulationDouglas W. Jones, Chien-Chun Chou, Debra Renk, Steven C. Bruell. 756-764 [doi]
• Limitation of optimism in the time warp operating systemPeter L. Reiher, Frederick Wieland, David R. Jefferson. 765-770 [doi]
• WATMIMS JIT/KANBAN benchmark summary and recommendationsKenneth N. McKay, Michael Rooks. 773-783 [doi]
• A visual simulation model of a workstation in a rolling mill facilityPierre A. Lefrançois, M.-H. Jobin, M.-C. Roy, G. Gamache. 784-789 [doi]
• Using simulation to explore potential improvements in an existing automated assembly systemC. J. Erickson. 790-794 [doi]
• Module modeling and economic optimization for large-scale AS/RSSoemon Takakuwa. 795-801 [doi]
• AS/RS amd warehouse modelingDaniel J. Muller. 802-810 [doi]
• A modular structure for a highly detailed model of semiconductor manufacturingSarah J. Hood, Amy E. B. Amamoto, Antonie T. Vandenberge. 811-817 [doi]
• Rapid modeling: in the design of a new PCB manufacturing systemKenneth R. Anderson, Gregory W. Diehl. 818-826 [doi]
• Combining software engineering principles with discrete event simulationBernard J. Schroer, Fan T. Tseng, Shou X. Zhang. 828-833 [doi]
• Integrating IBIS simulations and systems planning models through multiple model communicationsMichael G. Ketcham, R. Rajagopalan. 834-839 [doi]
• The next generation of manufacturing simulationC. Fuller. 840-842 [doi]
• Direct connect emulation and the project life cycleM. W. Hitchens, T. K. Ryan. 843-847 [doi]
• Using discrete-event computer simulation to test control systemsT. I. Miles, H. Siddeley. 848-858 [doi]
• Opportunities and challenges in manufacturing simulation for busy plant engineersKerim Tumay. 859-864 [doi]
• Implementation of rule-based technology in a shop scheduling systemD. P. Yancey, Scott Peterson. 865-873 [doi]
• Just-in-time simulation using artificial intelligenceS. Manivannan. 874-882 [doi]
• Intelligent back end of a goal directed simulation environment for discrete-part manufacturingS. Prakash, Robert E. Shannon. 883-891 [doi]
• Simulation and layout of a laser radar production facilityS. J. Lehman, W. R. Davison. 892-895 [doi]
• Simulation analysis of a flexible integrated chemical production facilityJohn E. Branstrator. 896-903 [doi]
• Simulation assisted design and installation of a flexible assembly systemJohn L. Ballard, Srivathsan Jagannathan, Randy Hartline, Bob Derksen. 904-907 [doi]
• The use of bottleneck starvation avoidance with queue predictions in shop floor controlC. Roger Glassey, Raja Pétrakian. 908-917 [doi]
• Dispatching in an integrated circuit wafer fabrication linePravin K. Johri. 918-921 [doi]
• Implementing the results of a manufacturing simulation in a semiconductor lineDavid J. Miller. 922-929 [doi]
• Expert simulation for on-line schedulingSanjay Jain, Karon Barber, David Osterfeld. 930-935 [doi]
• The user s role in a simulation based scheduling systemF. H. Grant, R. G. Lagoni. 936-941 [doi]
• Architecture for an integrated simulation /CIM systemsGordon M. Clark, David H. Withers. 942-948 [doi]
• The use of specialized modeling and display techniques in the simulation analysis of a newspaper mailroom distribution systemB. M. Werner. 951-956 [doi]
• A simulation model for Washington State juvenille detention facilitiesMinghui Yang. 957-962 [doi]
• Load sharing in hierarchical distributed systemsSayed Atef Banawan, John Zahorjan. 963-970 [doi]
• BLusseau, F.-a simulation annealing and resource location in computer networksFloriane Blusseau. 971-979 [doi]
• A simulation model of the NFS service on an Ethernet local area networkFloriane Blusseau. 971-979 [doi]
• Simulated annealing and resource location in computer networksG. Anandalingam. 980-988 [doi]
• The constraint method of attritionDean S. Hartley III. 989-996 [doi]
• Hail storm: a model for determining the survivability of fixed-wing aircraft against small armsJ. M. Grover. 997-1002 [doi]
• A comparison of serial and parallel processing simulation models of pilot workloadT. F. Schuppr. 1003-1009 [doi]
• The results of simulating a digital imaging network system in Echelon 3 of deployable combat medical facilitiesW. P. Johnson. 1010-1014 [doi]
• TCDL - an expert system language for wargamingJoseph L. Sowers, Paul E. Rubin. 1015-1021 [doi]
• A modeling perspective for meteor burst communicationBrian C. Healy, Wade H. Shaw Jr., Joseph R. Litko. 1022-1031 [doi]
• Efficient simulation of cache memoriesSandhya Dwarkadas, J. Robert Jump, James B. Sinclair. 1032-1041 [doi]
• Techniques for the trace-driven simulation of cache performanceSusan J. Eggers, Edward D. Lazowska, Yi-Bing Lin. 1042-1046 [doi]
• Simulation and analysis of a pipeline processorPhilip G. Emma, Joshua W. Knight, James H. Pomerence, Thomas R. Puzak, Rudolph N. Rechtschaffen. 1047-1057 [doi]
• NEST: a network simulation & prototyping testbedAlexander Dupuy, Jed Schwartz, Yechiam Yemini, David F. Bacon. 1058-1064 [doi]
• CLASS simulation of real time, highly compressed video transmission through an interference limited environmentR. Godfrey, R. Avant, D. Lai, J. Wang. 1065-1075 [doi]
• The use of modelling in long-range computer communications network planningR. K. Leighton. 1076-1084 [doi]
• Simulated real-time intersection signal controlE. C.-P. Chang. 1085-1091 [doi]
• An integrated simulation approach for design and analysis of timber harvesting sytemsSabah U. Randhawa, Eldon D. Olsen. 1092-1101 [doi]
• Reasoning in time and space: issues in interfacing a graphic computer simulation with an expert system for an intelligent simulation training systemLeslie D. Interrante, John E. Biegel. 1102-1106 [doi]
• Simulation modeling for emergency medical service systemsWafik H. Iskander. 1107-1111 [doi]
• Discrete simulation application-scheduling staff for the emergency roomA. P. Kumar, R. Kapur. 1112-1120 [doi]
• Computer simulation as a method for selecting nurse staffing levels in hospitalsM. L. McHugh. 1121-1129 [doi]
• Simulation with PC modelY. G. Chung, D. A. White. 1130-1136 [doi]