A stochastic programming approach for sawmill production planning
by Masoumeh Kazemi Zanjani; Daoud Ait-Kadi; Mustapha Nourelfath
International Journal of Mathematics in Operational Research (IJMOR), Vol. 5, No. 1, 2013

Abstract: This paper investigates a sawmill production planning problem where the non-homogeneous characteristics of logs result in random process yields. A two-stage stochastic Linear Programming (LP) approach is proposed to address this problem. The random yields are modelled as scenarios with discrete probability distributions. The solution methodology is based on the sample average approximation method. Confidence intervals are constructed for the optimality gap of several candidate solutions, based on Common Random Number (CRN) streams. A computational study including a prototype sawmill is presented to highlight the significance of using the stochastic model instead of the mean-value deterministic model, which is the traditional production planning tool in sawmills.

Online publication date: Mon, 31-Mar-2014

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 Mathematics in Operational Research (IJMOR):
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