Abstract

This paper is devoted to the application of the developed approach presented in Part I, to demonstrate its capability in tackling real-world MCDM problems. In this paper, a hypothetical case study of robotic flexible assembly cells (RFACs) is considered, to solve multi-objective optimization problems for dynamic scheduling. In order to find the optimal solution, a fuzzy decision support system (FDSS) is applied and built using the fuzzy logic toolbox in MATLAB software. The FDSS combines multi-objective functions in one performance measure named a multiple performance characteristics index (MPCI). The analysis results show that the developed approach is practical, works in RFACs setting, and deal with imprecise and uncertain information.

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