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Los Angeles, CA
March 31, 2009 to April 2, 2009
ISBN: 978-0-7695-3507-4
pp: 406-413
ABSTRACT
The overall performance of a supply-chain (SC) is influenced significantly by the decisions taken in its production-distribution (P-D) plan. A P-D plan integrates decisions in production, transport and warehousing as well as inventory management. One key issue in the performance evaluation of a Supply Network (SN) is the modeling and optimization of P-D planning problem considering its actual complexity. Based on the integration of Aggregate Production Planning and Distribution Planning, this paper firstly develops a mixed integer formulation for a two-echelon supply network considering the real-world variables and constraints. A multi-objective genetic algorithm (MOGA) is then designed for the optimization of the developed mathematical model. Finally, a real-world case study incorporating multiple products, multiple plants, multiple warehouses, multiple end-users, and multiple time periods will be considered for investigating the performance evaluation of the MOGA method against the traditional approaches of SC planning.
INDEX TERMS
Supply Chain Network, Production-Distribution Plan, Optimisation, Mixed Integer Programming Formulation, Genetic Algorithms
CITATION
Behnam Fahimnia, Lee Luong, Romeo Marian, "Optimization of a Two-Echelon Supply Network Using Multi-objective Genetic Algorithms", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 406-413, doi:10.1109/CSIE.2009.1007
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