Simulation Optimization Using Hybrid and Adaptive Metamodels

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Akhavan Niaki, Sahba | 2013

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 44476 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Mahlooji, Hashem
Abstract:
In this thesis we propose a new metamodel based simulation optimization algorithm using sequential design of experiments. The main objective is to have a new method which can be used without deep knowledge of different kinds of metamodels, optimization techniques and design of experiments. The method uses three metamodels simulataneously and gradually adapts to the best metamodel. In each iteration, some points are chosen as candidates for future simulation. These points are ranked based on the quality of metamodel prediction and their placement among simulated points, the best point will be chosen for simulation. Comparing the proposed algorithm with some of the popular simulation optimization methods in different test beds shows an acceptable performance of the new algorithm
Keywords:
Optimization ; Simulation ; Kriging Metamodel ; Regression Metamodel ; Radial Basis Function ; Sequential Experimental Design ; Simulation Optimization

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