You are here

Modeling strategic resource allocation in probabilistic global supply chain system with genetic algorithm

Download pdf | Full Screen View

Date Issued:
2003
Summary:
Effective and efficient supply chain management is essential for domestic and global organizations to compete successfully in the international market. Superior inventory control policies and product distribution strategies along with advanced information technology enable an organization to collaborate distribution and allocation of inventory to gain a competitive advantage in the world market. Our research establishes the strategic resource allocation model to capture and encapsulate the complexity of the modern global supply chain management problem. A mathematical model was constructed to depict the stochastic, multiple-period, two-echelon inventory with the many-to-many demand-supplier network problem. The model simultaneously constitutes the uncertainties of inventory control and transportation parameters as well as the varying price factors. A genetic algorithm (GA) was applied to derive optimal solutions through a two-stage optimization process. Practical examples and solutions from three sourcing strategies (single sourcing, multiple sourcing, and dedicated system) were included to illustrate the GA based solution procedure. Our model can be utilized as a collaborative supply chain strategic planning tool to efficiently determine the appropriate inventory allocation and a dynamic decision making process to effectively manage the distribution plan.
Title: Modeling strategic resource allocation in probabilistic global supply chain system with genetic algorithm.
82 views
26 downloads
Name(s): Damrongwongsiri, Montri.
Florida Atlantic University, Degree grantor
Han, Chingping (Jim), Thesis advisor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 2003
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 279 p.
Language(s): English
Summary: Effective and efficient supply chain management is essential for domestic and global organizations to compete successfully in the international market. Superior inventory control policies and product distribution strategies along with advanced information technology enable an organization to collaborate distribution and allocation of inventory to gain a competitive advantage in the world market. Our research establishes the strategic resource allocation model to capture and encapsulate the complexity of the modern global supply chain management problem. A mathematical model was constructed to depict the stochastic, multiple-period, two-echelon inventory with the many-to-many demand-supplier network problem. The model simultaneously constitutes the uncertainties of inventory control and transportation parameters as well as the varying price factors. A genetic algorithm (GA) was applied to derive optimal solutions through a two-stage optimization process. Practical examples and solutions from three sourcing strategies (single sourcing, multiple sourcing, and dedicated system) were included to illustrate the GA based solution procedure. Our model can be utilized as a collaborative supply chain strategic planning tool to efficiently determine the appropriate inventory allocation and a dynamic decision making process to effectively manage the distribution plan.
Identifier: 9780496568727 (isbn), 12056 (digitool), FADT12056 (IID), fau:8969 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (Ph.D.)--Florida Atlantic University, 2003.
Subject(s): Business logistics--Mathematical models
Physical distribution of goods--Management
Inventory control--Mathematical models
Genetic algorithms
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12056
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.