Flexible supply network planning for hybrid shipment: a case study of memory module industry

Li-Chih Wang, Chen-Yang Cheng and Wen-Kuan Wang

International Journal of Production Research, 2016, vol. 54, issue 2, 444-458

Abstract: The modern supply chain network has geographically spread out across the globe. The performance of a customer service level is highly dependent on the effectiveness of its supply chain planning. To improve the service provided to downstream customers, planners must not only decide order allocation among multiple distribution centres but also consider reducing the order-to-delivery time. Directed shipment delivery from manufacturing sites provides the flexibility of direct shipment; however, it also makes order allocation more difficult. In this study, a flexible supply network planning (FSNP) model based on integer linear programming is developed for the memory module industry. In addition to multisite order allocation planning, the FSNP model explicitly considers directed shipment from manufacturing sites for reducing the order-to-delivery time. Furthermore, the combination of characteristics of the memory module industry, such as multilevel and multisite production environments, multiple-to-multiple product structures, transportation and production lead times and capacity constraints, makes FSNP highly complicated. The results of the experiments reveal that the FSNP model improves supply chain planning regarding order due date and inventory and transportation costs.

Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2015.1133939 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:54:y:2016:i:2:p:444-458

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2015.1133939

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().