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Fuzzy-Logic Approach to Estimating the Fleet Efficiency of a Road Transport Company: A Case Study of Agricultural Products Deliveries in Kazakhstan

Igor Taran (), Asem Karsybayeva, Vitalii Naumov (), Kenzhegul Murzabekova and Marzhan Chazhabayeva
Additional contact information
Igor Taran: Department of Roads and Bridges, Rzeszow University of Technology, Powstańców Warszawy Ave. 12, 35959 Rzeszow, Poland
Asem Karsybayeva: Faculty of Logistics and Management, Academy of Logistics and Transport, Shevchenko Str. 97, Almaty 050022, Kazakhstan
Vitalii Naumov: Faculty of Civil Engineering, Cracow University of Technology, Warszawska Str. 24, 31155 Krakow, Poland
Kenzhegul Murzabekova: Faculty of Logistics and Management, Academy of Logistics and Transport, Shevchenko Str. 97, Almaty 050022, Kazakhstan
Marzhan Chazhabayeva: Faculty of Engineering, Yessenov University, Microdistrict 24, Building 2, Aktau 130000, Kazakhstan

Sustainability, 2023, vol. 15, issue 5, 1-14

Abstract: The estimation of the efficiency of road transport vehicles remains a significant problem for contemporary transport companies, as numerous stochastic impacts, such as demand stochasticity, road conditions uncertainty, transport market fluctuations, etc., influence the technological process. A fuzzy-logic approach is proposed to consider the uncertainty relating to estimating vehicle fleet efficiency. According to the developed approach, vehicle efficiency is described based on a membership function, whereas the efficiency of the whole vehicle fleet is evaluated as a fuzzy set. To demonstrate the developed approach, a case study is depicted for using cargo vehicles to deliver agricultural products in the Republic of Kazakhstan. The numeric results are presented for the selected models of vehicles that a transport company uses to service a set of clients located in Northern Kazakhstan: the transport services provided for each of the clients are characterized by numeric demand parameters—the consignment weight and the delivery distance. The completed calculations allowed us to obtain the membership functions for the alternative vehicle models and to present the transport company’s vehicle fleet as a fuzzy set.

Keywords: fleet structure; road transport; fuzzy logic; transport efficiency (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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