A bi-objective airline revenue management problem with possible cancellation
by Mohammad Vardi; Ali Salmasnia; Ali Ghorbanian; Hadi Mokhtari
International Journal of Applied Management Science (IJAMS), Vol. 8, No. 1, 2016

Abstract: The optimal allocation of seat inventory is a well-known problem of airline revenue management in the airline industry. It is usually carried out among fare classes with a known demand distribution for each class with the aim at increasing the efficiency of revenue systems and enhancing customer satisfaction. Furthermore, an important assumption is the issue of cancellation which is very common in the field of airlines. So to avoid having unused seat in a flight, overbooking technique is used. During last years, different approaches have been proposed for addressing this problem, but most of them only considered revenue to be maximised. In this paper, an optimisation approach based on Taguchi design of experiment and COPRAS decision-making method is proposed. The suggested method not only maximises total revenue and customer satisfaction simultaneously, but also mitigates the effects of nuisance factors on system by minimising the variance of two objectives. Experimental results on a standard example show the effectiveness of the proposed method.

Online publication date: Wed, 23-Mar-2016

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 International Journal of Applied Management Science (IJAMS):
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