A Fuzzy Order Promising Model With Non-Uniform Finished Goods

Abstract

Traditionally, the homogeneity of available units of the same finished good (FG) to be promised to customers has been assumed. However, contexts with lack of homogeneity in the product (LHP) are characterised by units of the same FG, which differ in some characteristics that are relevant for customers and give rise to different subtypes. For instance, in the ceramic industry, tiles are classified based on quality, tone and gage, because of functional and aesthetical reasons related to their joint installation. LHP imposes new constraints in the order promising process because customers need homogeneous units. However, the final amount of the homogeneous units in planned lots is uncertain when promising orders, because they will only be known once produced and classified. In this sense, we introduce homogeneity constraints including fuzzy sets; specifically, we address the interaction among fuzzy homogeneity coefficients that represent the fraction of each homogeneous sublot. Therefore, modelling uncertainty in interdependent technological coefficients in a dynamic context is one of the main novelties of our proposal. Thus, in this paper, in order to reliably meet the homogeneity required by customers, a fuzzy model is proposed to support the promising process in LHP contexts after taking into account uncertainty in planned homogeneous sublots. The fuzzy model is translated into an alpha-parametric equivalent crisp model. Here, it is important to highlight another important novelty of the paper related to the proposed methodology to analyse the suitability of the minimum degree of possibility (the -cut), by an adapted TOPSIS-based fuzzy procedure. Finally, the experimental design, which is inspired in the ceramic sector, proves both the validity of the model and a better performance of the fuzzy model compared to the deterministic one, in several executions with forecasts of the real size of homogeneous sublots.