A reconfiguration optimisation model for hub-and-spoke network mergers
by Qing-Mi Hu
European J. of Industrial Engineering (EJIE), Vol. 11, No. 1, 2017

Abstract: Reconfiguring the merged hub-and-spoke networks (HSNs) improves the efficiency of logistics operations by optimally integrating logistics service resources. Typically, the reconfiguration of HSN focuses on minimising the operating cost, while ignoring service level and environmental considerations. This paper develops a novel optimisation strategy for HSN mergers problem, in which vehicle speeds are formulated as decision variables of a nonlinear multi-objective mixed-integer programming model that considers the vehicle emissions cost, on-time delivery cost and operating cost. To overcome the nonlinear complexity, the formulated model is transformed into a second-order mixed-integer cone programming model. Furthermore, the trade-offs between the vehicle emissions cost, on-time delivery cost and operating cost are analysed. The experimental results demonstrate that the new HSN optimisation strategy with vehicle speeds as the decision variables can significantly reduce the vehicle emissions cost, on-time delivery cost, and operating cost. [Received: 16 December 2015; Revised: 14 April 2016; Revised: 26 July 2016; Accepted: 29 July 2016]

Online publication date: Sat, 07-Jan-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the European J. of Industrial Engineering (EJIE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com