Designing a fuzzy rule-based system for selecting the proper lot-sizing technique

In this paper, we implement a system for selecting the proper lot-sizing technique based on Fuzzy Inference Systems (FIS). Among ten commonly known lot-sizing techniques, this FIS considers Input variables such as set-up cost, holding cost, planning horizon, lumpiness and BOM level which are modeled as linguistic variables by using fuzzy sets. The strength of the model is the priority level that is allocated to each technique as the output variables. The other strength of this method is use of some advises that were recommended by previous researchers through linguistic terms. This FIS considers all these individual advises in one inference system. The work is accompanied by two examples that show how to apply this approach. The model is developed using MATLAB software.