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Optimization of a Two-Echelon Supply Network Using Multi-objective Genetic Algorithms

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3 Author(s)
Fahimnia, B. ; Sch. of Adv. Manuf. & Mech. Eng., Univ. of South Australia, Mawson Lakes, SA, Australia ; Luong, L. ; Marian, R.

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.

Published in:

Computer Science and Information Engineering, 2009 WRI World Congress on  (Volume:5 )

Date of Conference:

March 31 2009-April 2 2009