Venture capital project selection based on interval number grey target decision model

• Published in: Soft computing (Berlin, Germany) Vol. 25; no. 6; pp. 4865 - 4874
• Main Authors: Fu, Sha, Xiao, Ye-zhi, Zhou, Hang-jun, Liu, Sheng-zong
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2021; Springer Nature B.V
• Subjects: Artificial Intelligence; Computational Intelligence; Control; Decision making; Engineering; Fuzzy sets; Goal programming; Linear programming; Linear transformations; Mathematical Logic and Foundations; Mechatronics; Methodologies and Application; Methods; Project feasibility; Robotics; Statistical analysis; System theory; Uncertainty analysis; Vector analysis; Comprehensive off-target distance; Positive and negative clouts; Interval number; Grey target decision; Goal programming
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-020-05495-2

In this study, aiming at the multi-attribute decision-making problem with incomplete and uncertain attribute weight information and attribute value of interval numbers, a grey target decision-making model of interval numbers based on positive and negative clouts is proposed. Firstly, in this model, the linear transformation operator of interval number is used to normalize the original decision information, and the positive and negative clouts of interval number are designed. Secondly, after the space projection distance between each scheme and the positive and negative clouts is considered comprehensively, the off-target distance is taken as the basis of vector analysis in space to obtain a new comprehensive off-target distance. The existing interval number grey target decision-making model ignores the important influence of interval distribution and the correlation between the attributes in scheme evaluation, and there are some fuzzy errors when setting the weight of attributes. In order to solve the above problems, this paper combined with the uncertainty analysis of the attribute weights, a goal programming is constructed for the objective function based on the comprehensive off-target distance minimization to solve the attribute weight vector, and finally determine the order of the scheme. Finally, the feasibility and effectiveness of the proposed grey target decision model are verified by an example of venture capital projects. Compared with traditional models, the improved model fully considers the characteristics of interval data and the correlation between the attributes.