An aggregation framework for time series-based MCDA

Multiple criteria decision analysis (MCDA) is an important part of modern decision science. This paper is devoted to investigating the time series-based multiple criteria decision analysis (TSMCDA) problems where the decision information is provided by decision maker(s) at different time periods. First, we define the concept of ordered weighted averaging (OWA) and based on the OWA aggregation method. Next, a hybrid approach integrating OWA aggregation is proposed to tackle TS MCDA problems. Then, a numerical example is provided to demonstrate the proposed approach and the results are compared for different aggregation settings and confirm the rankings from different scenarios.