Shipment size and vehicle choice modeling for road freight transport: A geographical perspective

Comparison of the Relative Importance of Factors Affecting the Conveyance of Bulk and Liquid Cargo

“…This comparison facilitates the refinement of subsequent modeling procedures for the transportation of liquid and bulk cargoes under more appropriate rough circumstances, after an assessment of the unique characteristics associated with said cargo transportation. The utilization of these methodologies enables a more comprehensive evaluation of the variables influencing road freight transportation [20]. This approach enables the mitigation of transportation risks, the optimization of vehicle design for transportation processes, and the simultaneous attainment of economic benefits (through the identification of transportation costs) and en-vironmental protection (by evaluating the characteristics of individual cargo transportation and potential traffic incidents that may result in environmental harm).…”

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

“…In relation to the European Union, such form of transport as "doortodoor" service is considered one of the most suitable solutions capable of curb ing the unsustainable growth of the transport sector. Solving such common problems as choosing the optimal shipment size and a freight vehicle (by using modeling approach [19]), se lecting of a freight forwarder (by developing a multicriteria decisionmaking system [20]), analysis of a shipper's decision to delegate the choice of transport mode to service providers (by carrying out a survey [17]), evaluating the quality of the transportation infrastructure (by utilizing navigation service data [21]), exploring the notion of monopolistic competition (by implementing an agentbased framework for freight mar ket interactions [22]), etc. also contribute to increasing the level of sustainable transportation and mobility.…”

“…It should also be noted that the latest development of infor mation technologies and artificial intelligence allows the use of innovative tools to solve both classic and modern transport problems and tasks. Some of the most popular techniques used by scientists include: agentbased modeling and goal program ming [22,23]; a hybrid system for strategic planning, which integrates mathematical models with knowledge principles [9]; covariance analysis, discrete choice and latent class analysis [17,19]; tabu search heuristics [11]; deep and machine learning [8,[14][15][16]; mechanisms of fuzzy logic and simulated anneal ing [12]; methods based on the data of navigation services [21]; exploratory factor analysis [5]; innovative combination of intu itionistic fuzzy numbers with graphtheoretic and matrix ap proach [6]; models of commoditybased freight demand based on exogenous economic forecasts [24] and economics of trans action costs [8]; the theory of time windows [7], dynamic mea surements [25], digital image correlation method [26] and the Bayesian approach for model estimation [27,28].…”