A New Approach Using Dynamic Group Decision Making for Selection of Multiple Alternatives Under Risk and Uncertainty

The preferences of decision maker are dynamic changing in collaborative process under uncertainty. Dynamic Group Decision Making is to consider uncertainty measures in the processes of multiple decisions for the selection of alternatives. The aim of this study is to present a new approach using dynamic group decision making, together with expert sensibilities to assist the selection of multiple alternatives (companies, stocks, and company groups) and reduce risky decisions under uncertain conditions. The proposed approach aims to aggregate expert preferences and sensibilities, quantified by Self-Organizing Map (SOM) in order to select appropriate alternatives under risk and uncertainty for optimal solutions in dynamic environments. To confirm the model's performance, the proposed approach has been tested and validated in practice with trading investment systems. The experiments, through case studies, show that the new approach, applying the model for quantification of expert sensibilities, together with Common Sense Human Reasoning enhances the capability for the selection of alternatives at the right time to achieve the greatest investment returns, and reduces losses to deal with various domains in dynamic environments.