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A METHODOLOGY FOR MINIMIZING THE OSCILLATIONS IN SUPPLY CHAINS USING SYSTEM DYNAMICS AND GENETIC ALGORITHMS

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Date Issued:
2005
Abstract/Description:
Supply Chain Management (SCM) is a critically significant strategy that enterprises depend on to meet challenges that they face because of highly competitive and dynamic business environments of today. Supply chain management involves the entire network of processes from procurement of raw materials/services/technologies to manufacturing or servicing intermediate products/services to converting them into final products or services and then distributing and retailing them till they reach final customers. A supply chain network by nature is a large and complex, engineering and management system. Oscillations occurring in a supply chain because of internal and/or external influences and measures to be taken to mitigate/minimize those oscillations are a core concern in managing the supply chain and driving an organization towards a competitive advantage. The objective of this thesis is to develop a methodology to minimize the oscillations occurring in a supply chain by making use of the techniques of System Dynamics (SD) and Genetic Algorithms (GAs). System dynamics is a very efficient tool to model large and complex systems in order to understand their complex, non-linear dynamic behavior. GAs are stochastic search algorithms, based on the mechanics of natural selection and natural genetics, used to search complex and non-linear search spaces where traditional techniques may be unsuitable.
Title: A METHODOLOGY FOR MINIMIZING THE OSCILLATIONS IN SUPPLY CHAINS USING SYSTEM DYNAMICS AND GENETIC ALGORITHMS.
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Name(s): LAKKOJU, RAMAMOORTHY, Author
RABELO, LUIS, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2005
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Supply Chain Management (SCM) is a critically significant strategy that enterprises depend on to meet challenges that they face because of highly competitive and dynamic business environments of today. Supply chain management involves the entire network of processes from procurement of raw materials/services/technologies to manufacturing or servicing intermediate products/services to converting them into final products or services and then distributing and retailing them till they reach final customers. A supply chain network by nature is a large and complex, engineering and management system. Oscillations occurring in a supply chain because of internal and/or external influences and measures to be taken to mitigate/minimize those oscillations are a core concern in managing the supply chain and driving an organization towards a competitive advantage. The objective of this thesis is to develop a methodology to minimize the oscillations occurring in a supply chain by making use of the techniques of System Dynamics (SD) and Genetic Algorithms (GAs). System dynamics is a very efficient tool to model large and complex systems in order to understand their complex, non-linear dynamic behavior. GAs are stochastic search algorithms, based on the mechanics of natural selection and natural genetics, used to search complex and non-linear search spaces where traditional techniques may be unsuitable.
Identifier: CFE0000683 (IID), ucf:46489 (fedora)
Note(s): 2005-08-01
M.S.
Engineering and Computer Science, Department of Industrial Engineering and Management Systems
Masters
This record was generated from author submitted information.
Subject(s): supply chain
system dynamics
genetic algorithms
optimization
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0000683
Restrictions on Access: public
Host Institution: UCF

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