Optimization of a two-echelon supply network using multi-objective genetic algorithms

Publisher:
IEEE Computer Society
Publication Type:
Conference Proceeding
Citation:
2009 WRI World Congress on Computer Science and Information Engineering, 2009, 5 pp. 406 - 413
Issue Date:
2009-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2012008283OK.pdf428.23 kB
Adobe PDF
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 twoechelon 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.
Please use this identifier to cite or link to this item: