@article {10.3844/ajeassp.2017.156.164, article_type = {journal}, title = {New Strategy to Optimize Lean Supply Chain Design by Meta-Heuristic}, author = {Nguyen, Thi Hong Dang and Dao, Thien My}, volume = {10}, number = {1}, year = {2017}, month = {Mar}, pages = {156-164}, doi = {10.3844/ajeassp.2017.156.164}, url = {https://thescipub.com/abstract/ajeassp.2017.156.164}, abstract = {This paper aims at presenting one novel quantitative strategy of optimizing the design of Lean supply chain using Meta-Heuristics. While classifying Lean Manufacturing tools in two categories, namely Functional and Tier Lean tools, we propose a new framework to design the Lean supply chain by implementing the former into a 5-echelon Fat supply chain. As the following step, we investigate the effect of the latter on the mentioned Lean supply chain model. Then, we utilize the tight correlation of Tier Lean tools and priority-based Genetic Algorithm Meta-Heuristics in order to optimize the configuration of the Lean supply chain. Finally, these ideas are illustrated step by step in one numeral example.}, journal = {American Journal of Engineering and Applied Sciences}, publisher = {Science Publications} }