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...
Cataloging briefA 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...
Find in contentBookmark
|
|