Using Time Series and Classification in Vehicle Routing Problem

doi:10.23940/ijpe.21.01.p2.1425

Abstract

Abstract:

The purpose of data mining is to process raw data and extract rules. The Vehicle Routing Problem is a logistical problem, which handles the delivery and the collection of products. In the classical problem, the position of the depot and customers are known in advance. In case of the base problem, the demand of the customer is also known in advance. But, we may need some future data, for example, the demand of the customer, so we need to forecast these data from the previous data. After the determination of the future demands of the customers, we determined whether it is worth serving customers or not with the help of the classification methods. After the time-series forecasting and classification, we also determined the route of the vehicles with the help of the genetic algorithm.

Key words: logistic, data mining, vehicle routing problem, time-series forecasting, classification

Anita Agárdi, László Kovács, and Tamás Bányai. Using Time Series and Classification in Vehicle Routing Problem [J]. Int J Performability Eng, 2021, 17(1): 14-25.

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