AI-based project risk management process for a kind of manufacturing alliance
by Hongyi Cao
International Journal of Manufacturing Technology and Management (IJMTM), Vol. 13, No. 1, 2008

Abstract: In this paper, an artificial intelligence-based project risk management process is proposed to implement quantitative risk management for a kind of manufacturing alliance in the agile manufacturing environment. After the literature review, a multiphase project risk management process is formed consisting of risk analysis, risk evaluation and risk control. Probability Risk Analysis is used as the main quantitative risk analysis technique. Some forms of mathematical programming models are formulated in risk evaluation and risk control phases. Because of the complexity, non-linearity, multiobjective stochastic constraints or interval or fuzzy coefficients of these models, they cannot be solved easily by conventional methods. Genetic algorithms are designed. A real life example is also given and the computational results illustrate the efficiency of the algorithms.

Online publication date: Sun, 02-Dec-2007

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 Manufacturing Technology and Management (IJMTM):
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