An stochastic multiattribute acceptability analysis‐based method for the multiattribute project portfolio selection problem with rank‐level information. Issue 5 (23rd June 2019)

• Record Type: Journal Article
• Authors: Song, Shiling; Ang, Sheng; Yang, Feng; Xia, Qiong
• Other Names: Xu Zheng guestEditor.; Liu Yunhuai guestEditor.
• Is Part Of: Expert systems. Volume 36:Issue 5(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-06-23
• Subjects: project portfolio selection -- project management -- stochastic multiattribute acceptability analysis -- multiattribute decision analysis; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12447
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: In many cases of practical multiattribute project portfolio selection problems, it is hard to obtain accurate measurements of attributes and precise preference information. Even after a long and costly information gathering, the attribute measurements and the preference information can still be uncertain or inaccurate. Considerable cost saving will be obtained if the selection of an optimal project portfolio can be done using rank‐level information based on some or all the attributes, without knowing the preference information. In this paper, we propose a stochastic multiattribute acceptability analysis‐based method that can deal with mixed rank and cardinal attribute measurements and uses little or no weight information. In the proposed stochastic multiattribute acceptability analysis‐based method, the decision makers need not to express their preferences explicitly or implicitly, so it is particularly useful when no weight information is available at all. A numerical example involving selection of photovoltaic plants in an industrial province in Eastern China is provided to demonstrate the proposed method.