Int J Performability Eng ›› 2021, Vol. 17 ›› Issue (1): 14-25.

• Orginal Article •

Using Time Series and Classification in Vehicle Routing Problem

Anita Agárdia*, László Kovácsa,  and Tamás Bányaib

1. aInstitue of Informatics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary
bInstitue of Logistics, University of Miskolc, 3515 Miskolc-Egyetemváros, Hungary
• Submitted on  ;  Revised on  ; Accepted on
• Contact: * Corresponding author. E-mail address: agardianita@iit.uni-miskolc.hu
• About author:
Anita Agárdi is an assistant lecturer of the University of Miskolc. Her research interests include optimization algorithms and logistics.
László Kovács is a professor of the University of Miskolc. His research interests include data mining, ontology and optimization.
Tamás Bányai is an associate professor of the University of Miskolc. His research interests include logistics and supply chain management.

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.