Authors: Hongyi Cao
Addresses: School of Business Administration, ZhongNan University of Economics and Law, WuHan, HuBei 430060, PR China
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.
Keywords: risk management; virtual organisation; genetic algorithms; agile manufacturing; artificial intelligence; manufacturing alliance; risk analysis; risk evaluation; risk control; one-of-a-king manufacturing; China; manufacturing project management.
International Journal of Manufacturing Technology and Management, 2008 Vol.13 No.1, pp.95 - 110
Published online: 02 Dec 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article