A possibilistic programming approach for capacitated lot-sizing problem in mixed assembly shops
by Navid Sahebjamnia; Yalda Yahiazadeh Andavari; Zahra Safaie Koleti; Hamed Gholami Orimi
International Journal of Applied Decision Sciences (IJADS), Vol. 6, No. 4, 2013

Abstract: This paper develops a fuzzy multi-objective linear programme (FMOLP) model for solving the bi-objective capacitated lot-sizing problem (CLSP). The proposed model attempts to simultaneously minimise total cost consist of total production variation cost, inventory cost, backlog cost and total setup cost while maximising the resource utilisation. According to the structure of the mixed assembly shops, a multi-product model with multi-item that should be produced during multi-level has been designed. Based on the vagueness and imprecision of the real case, the production, holding and backorder costs and demand of the products were considered as fuzzy number that have their membership function during planning horizon in each period. An interactive fuzzy solution method is developed by combining a number of efficient solution algorithms from the recent literature in order to solve the proposed possibilistic model. In order to demonstrate the significance and applicability of the proposed model as well as the usefulness of the proposed solution approach, numerical experiments are conducted and the results are provided.

Online publication date: Thu, 28-Nov-2013

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 Decision Sciences (IJADS):
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