318
Views
18
CrossRef citations to date
0
Altmetric
Articles

Network reliability with deteriorating product and production capacity through a multi-state delivery network

, &
Pages 6681-6694 | Received 29 Jun 2013, Accepted 16 Mar 2014, Published online: 28 Apr 2014
 

Abstract

Delivery process is a critical issue from the viewpoint of supply chain management. However, in the delivery process, deterioration would occur because of natural disasters (e.g. earthquake, fire, flood, hurricane and landslide) or man-made factors (e.g. explosion, terrorist attack and vehicular collision). The results in the intact products arriving at the market may not satisfy the demand. This paper thus concentrates on a multi-state delivery network (MSDN) with multiple suppliers, in which a vertex denotes a supplier, a transfer station or a market, while a branch denotes a carrier providing the delivery service for a pair of vertices. The available capacity of the carrier responsible for the delivery on a branch is multi-state because the capacity may be partially reserved by other customers. The addressed problem is to evaluate the network reliability, the probability that the MSDN with the deterioration consideration can satisfy the market demand within the budget and production capacity limitations. An algorithm is developed in terms of minimal paths to evaluate the network reliability along with a numerical example to illustrate the solution procedure. A real case study of the deteriorating auto glass is utilised to demonstrate the utility of the proposed algorithm.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 973.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.