Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
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.
Supply Chain Network, Production-Distribution Plan, Optimisation, Mixed Integer Programming Formulation, Genetic Algorithms
Romeo Marian, Behnam Fahimnia, Lee Luong, "Optimization of a Two-Echelon Supply Network Using Multi-objective Genetic Algorithms", Computer Science and Information Engineering, World Congress on, vol. 05, no. , pp. 406-413, 2009, doi:10.1109/CSIE.2009.1007