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Development of an Algorithm for Optimizing the Digital Computer Simulation Experiments

Omranpour, Zohreh | 2012

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 43070 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Ghasemi Tari, Farhad
  7. Abstract:
  8. simulation models are free of any restricting assumptions which may normally be considered in a stochastic system, so simulation is considered as one of the most popular tools that can be applied toward analysis of behavior of stochastic systems which are complex.
    In order to analyze such problems and determine the best combination of input variables to optimize the system performance criterion, simulation optimization methods were introduced. The most important issue in these problems is that simulation models are usually considered as the black-box models in which, the output function is not usually expressed explicitly.
    This work reviews different methods which developed for solving simulation optimization problems and presents a new algorithm for solving continues simulation optimization problems which are unconstrained and large-scale. This algorithm especially address the simulation optimization problems for which the objective function is evaluated by running expensive simulation experiments .The proposed algorithm developed based upon a metamodel based method using stochastic kriging metamodels. It also benefit of a sequential experiment design and a hybrid algorithm based on nested partition method which is improved using particle swarm optimization algorithm.
    The proposed simulation optimization algorithm rely on very few number of simulation runs. This issue can be crucial factor for a simulation optimization algorithm as the most real world problems have expensive simulation models
  9. Keywords:
  10. Simulation Optimization ; Sequential Experimental Design ; Particles Swarm Optimization (PSO) ; Stochastic Kriging Metamodel ; Nested Partition Algorithm

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