A revised weighted sum decision model for robot selection

We present a revised weighted sum model that incorporates the values assigned by a group of experts on different factors in selecting robots. The model reduces the impact of any decision maker, with a vastly different opinion, on the overall decision. Using this model, the highest and lowest expertsʹ values on the weights and the subjective factors are eliminated in this comprehensive method for robot selection. A numerical example is presented to illustrate the model and to show a rank reversal when compared to a model that does not eliminate extreme values.