Loading...
Search for:
stochastic-kriging-metamodel
0.005 seconds
A Stochastic Kriging Metamodel for Constrained Simulation Optimization Based on a k-Optimal Design
, M.Sc. Thesis Sharif University of Technology ; Mahlooji, Hashem (Supervisor)
Abstract
In recent years, optimization via simulation for the systemswhose objective function has stochastic characteristic and doesn’t explicitly exist in closed form, has attracted considerable interest.Simulation of this kind of systems at times may be veryexpensive. In this research, the constraint simulation optimization problem is considered for solving problems with stochastic features based on metamodels. For this purpose, stochastic Kriging is used as a metamodel. In this method, first, a few feasible points in the solution space are identified by thek-optimal design of experiment and then the simulation runs are performed. In the next step, a metamodel is fitted to all the stochastic...
Development of an Algorithm for Optimizing the Digital Computer Simulation Experiments
, M.Sc. Thesis Sharif University of Technology ; Ghasemi Tari, Farhad (Supervisor)
Abstract
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...
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...