The Integration Model of Closed-Loop Supply Chain Resource Allocation Considering Remanufacturing

Abstract

Logistics resource planning is an integration model of materials requirement planning and distribution resource planning which is a resource allocation technology. It is a technology of satisfying both production material supply and resource allocation optimization which is based on inventory management. For the remanufacturing supply chain, recycling and rebuilding of products form a reverse materials movement loop which challenges the traditional logistics resource planning system. For the characteristics of reverse logistics of remanufacturing supply chain, we propose a closed-loop supply chain resource allocation model based on autonomous multi-entity. We focus on integration resource allocation model of materials requirement planning and distribution resource planning considering remanufacturing.

Keywords

remanufacturing / supply chain / reverse logistics / resource allocation / integration model

References

[1] Atasu, A., Van Wassenhove, L.N., & Sarvary, M. (2009). Efficient take-back legislation. Production and Operations Management, 18, 243–258

[2] Bras, B., & Mcintosh, M. W. (1999). Product, process and organization design for remanufacture—an overview research. Robots and Computer Integrated Manufacturing, 167–178.

[3] Chen, Q. (1997). MRP II Manufacturing Resource Planning Basis. Beijing: Enterprise Management Publishing Group.

[4] Gao, H. (2009). Workshop logistics intelligent control and warehouse management system research. Hubei: Huazhong University of Science and Technology.

[5] Guo, J. (2011). Warehouse and MRP-II management Q & A. Guangzhou: Guangdong Provincial Publishing Group.

[6] Han, J., Wu, C., & Fan, Y. (1998). Status and developing trends of supply chain modeling and management technology. CIMS, 4, 8–13.

[7] Li, Y., & Long, W. (2012). The integration model of supply chain resource allocation—LRP. International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) Proceedings, 1279–1285.

[8] Wang, Q., Liu, F., & Huang, H. (2008). Service oriented discrete workshop reconfigurable manufacturing execution system research. Computer Integrated Manufacturing, 4, 737–743.

[9] Yuan, C., & Liu, H. (2007). Logistics, Warehousing and Distribution Management. Beijing: Peking University Press.

[10] Zhang, Y. (1997). MRP-II and its Application. Beijing: Tsinghua University Press.

[11] Zhu, X., & Pan, . (2000). Mix the multi-objective optimization design variables of Pareto genetic algorithm to realize. Journal of Shanghai Jiao Tong University, 411–414.

RIGHTS & PERMISSIONS

2016 The Author(s) 2016. This article is published with open access at engineering.cae.cn