Abstract
This research investigates multi-criteria dispatching problems with unknown user preference functions to help decision makers (DMs) find solutions that meet their multi-criteria preferences. The explicit consideration of the following factors distinguish this research from previous literature: (1) dispatching management with three conflicting objectives, (2) nonlinear preference functions with unknown weights, (3) indecisive threshold that models the bounded rationality of DMs, and (4) near optimal solution through a small number of interactions. In a smart factory of Industry 3.5, the proposed interactive centroid method (ICM) enhances the efficiency of human–computer interaction and improves the quality of multi-criteria manufacturing decisions significantly. Our extensive numerical study reveals that the ICM algorithm finds near optimal solutions under linear or quadratic utility functions through less than a dozen interactions with DMs. The average gap between the ICM solutions and true optimal is merely 1.537% and 0.882% under quadratic and linear utility functions, respectively.
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