Title

Decision Support Under Uncertainties Based On Robust Bayesian Networks In Reverse Logistics Management

Keywords

Bayesian network; Imprecise probability; Interval analysis; Plm; Product lifecycle management; Reverse logistics

Abstract

One of the major challenges for product lifecycle management systems is the lack of integrated decision support tools to help decision-making with available information in collaborative enterprise networks. Uncertainties are inherent in such networks due to lack of perfect knowledge or conflicting information. In this paper, a robust decision support approach based on imprecise probabilities is proposed. Robust Bayesian belief networks with interval probabilities are used to estimate imprecise posterior probabilities in probabilistic inference. This generic approach is demonstrated with decision-makings in design for closed-loop supply chain. The ultimate goal of robust intelligent decision support systems is to enhance the effective use of information available in collaborative engineering environments. Copyright © 2009 Inderscience Enterprises Ltd.

Publication Date

1-1-2009

Publication Title

International Journal of Computer Applications in Technology

Volume

36

Issue

3-4

Number of Pages

247-258

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1504/ijcat.2009.028047

Socpus ID

70349131482 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/70349131482

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