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The Scientific World Journal
Volume 2013 (2013), Article ID 202085, 8 pages
http://dx.doi.org/10.1155/2013/202085
Research Article

A Method to Dynamic Stochastic Multicriteria Decision Making with Log-Normally Distributed Random Variables

1School of Science, Hunan University of Technology, Zhuzhou 412007, China
2School of Business, Central South University, Changsha 410083, China

Received 4 August 2013; Accepted 22 August 2013

Academic Editors: A. Amirteimoori and S. W. Chiu

Copyright © 2013 Xin-Fan Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

We investigate the dynamic stochastic multicriteria decision making (SMCDM) problems, in which the criterion values take the form of log-normally distributed random variables, and the argument information is collected from different periods. We propose two new geometric aggregation operators, such as the log-normal distribution weighted geometric (LNDWG) operator and the dynamic log-normal distribution weighted geometric (DLNDWG) operator, and develop a method for dynamic SMCDM with log-normally distributed random variables. This method uses the DLNDWG operator and the LNDWG operator to aggregate the log-normally distributed criterion values, utilizes the entropy model of Shannon to generate the time weight vector, and utilizes the expectation values and variances of log-normal distributions to rank the alternatives and select the best one. Finally, an example is given to illustrate the feasibility and effectiveness of this developed method.