Fuzzy Sets for Purchase Planning in Uncertain Conditions
This work is devoted to the development of models and algorithms for purchase planning problem. For accurate and flexible purchasing it is important to be able to effectively combine input data from various types of sources. This paper proposes a method based on fuzzy sets to solve the problem of effective exploitation of expert knowledge and statistics of demand to determine the optimal amount of a purchase order. A membership function is used to model demand for a product. This membership function can be built using statistics, expert knowledge, or both. After membership functions for each product are created, purchasing optimization takes place based on these functions. The proposed approach supports decision making process based on formal methods of fuzzy, uncompleted or permanently changing information. The developed models and algorithms can be used for optimum assortment determination of enterprises involved in production and distribution of various types of goods.