Analysis of the dealer car service spare range using the FP-Growth algorithm

Abstract

In the current conditions of instability and a rapidly changing economy, mathematical methods and intelligent information technologies used in making managerial decisions in various fields play an important role. It is especially necessary to approach carefully the process of securing stocks of products sold, which is necessary for the profit of a car service company. The company in its activity requires a wide range of cars spare parts. The lack of necessary parts can provoke a long downtime of cars waiting for the technical maintenance or the customer's refusal from service. Excess parts that have not been sold for a long time require increased storage costs. In this article, the FP-Growth algorithm is used to analyze the range of cars spare parts for dealer car service company, which solves the problem of finding associative rules. This task is based on searching in a large volume of source data for relationships in the form of if X, then Y. The FP-Growth algorithm differs from other methods of searching for associative rules by the procedure of constructing a tree of variants of sets of objects, which allows to reduce the search for possible variations and reduce the number of iterations. To implement the proposed algorithm, the Loginom Community analytical system was used. As a result, sets of spare parts were identified, often used together in the current repair of cars.