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- W768630218 abstract "The aim of the research was to assist non-experts produce meaningful, non-terminating discrete event simulations studies. The exemplar used was manufacturing applications, in particular sequential production lines. The thesis addressed the selection of methods for introducingrandomness, setting the length of individual simulation runs, and determining the conditions for startingmeasurements. Received wisdom in these aspects of simulation experimentation was not accepted.The researchmade use of a Markov Chain queuing model and statistica analysis of exhaustive computer-based experimentation using test models. A specific production-line modeldrawn from the motor industry was used as a point of reference. A distinctive,quality control like, process of facilitating the controlled introduction of randomness from a pseudo random-number generator was developed, rather than relying on a generator's a priori performance in standard statistical tests of randomness. This approach proved to be effective and practical.Other results included: The distortion in measurements due to the initial conditions of a simulation run of a queuewas only corrected by a lengthy run and not by discarding early results. Simulation experiments of the same queue, demonstrated that a single long run gave greater accuracy than having multiple runs. The choice of random number generator is less important than the choice of seed. Notably, RANDU (a discreditedMLCG) with careful seed selection was able to outperform in tests both real randomnumbers, and other MLCGs if their seed were chosen randomly,99.8% of the time. Similar results were obtained for Mersenne Twister and Descriptive Sampling.DescriptiveSamnpling was found to provide the best samples and was less susceptible to errorsin the forecast of the required sample size. A method of determining the run length of the simulation that would ensure the run was of the true condifions was proposed. An interactive computer program was created to assist in the calculation of the run length of a simulation and determine seeds so as to obtain highly representative samples, demonstrating thefacility required in simulation software to support theses elected methods." @default.
- W768630218 created "2016-06-24" @default.
- W768630218 creator A5065411539 @default.
- W768630218 date "2003-06-01" @default.
- W768630218 modified "2023-09-26" @default.
- W768630218 title "Evaluation of alternative discrete-event simulation experimental methods" @default.
- W768630218 hasPublicationYear "2003" @default.
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