A Robust Metamodel-based Simulation Optimization Approach for a Multi-Product Supply Chain Problem

Please enable javascript in your browser.

Sharifnia, Mohamad Ebrahim | 2014

674 Viewed

Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 45390 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Mahlooji, Hashem
Abstract:
One of the popular problems in the area of supply chain management is how to determine the critical decision variables in supply chain systems. This problem has been investigated by means of various methods one of which is simulation optimization. Due to the uncertain nature of real world systems, robustness of the resulting solutions is a worthy issue to be considered. In this effort, the problem of determining the safety stock levels in a multi-product supply chain system is addressed, a proper framework to define the decision and environmental variables is proposed, and their effects on the performance measures is investigated. A robust metamodel based simulation optimization approach based on Taguchi’s view is suggested to optimize a multi-product supply chain problem. In the process, performance of two popular metamodeling methods, namely Kriging and artificial neural networks, is compared
Keywords:
Simulation Optimization ; Supply Chain ; Safety Stock ; Metamodel ; Robust Optimization

No TOC