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

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.

Shaping sustainable strategies of freight forwarding companies in the environment of the road transport market

“…The main purpose of forwarding is the uninterrupted movement of cargo between interested parties. For this, freight forwarders must perform an extremely complex set of techno logical and organizational operations that ensure the continu ous, reliable, and flexible functioning of supply chains [1,2], as well as documentary support for the transportation process. In turn, logistics service providers usually work based on or ders from cargo owners, which in most cases are unstable [3,4], as they depend on various circumstances.…”