Optimization Method and Software for Fuel Cost Reduction in Case of Road Transport Activity

Kovács, György

doi:10.14311/ap.2017.57.0201

Cited by 6 publications

(2 citation statements)

References 6 publications

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“…The cost of fuel is normally the largest of all the transportation costs [9,23]. Fuel is a particularly significant cost in agriculture due to two major reasons.…”

Section: Interest On Capitalmentioning

confidence: 99%

Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm

2019

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Improving the performance and economic sustainability of agricultural producers requires the integration of many dimensions, one of which is logistics. Establishing efficient and cost-effective transportation is a key element of establishing sustainable linkages along food supply chains between farmers, storage and transport companies, and consumers. In this regard, infrastructural constraints to sustainability in agricultural production exacerbate transportation costs and risks, and thus result in lower performance of agricultural producers. As fuel consumption is, first, the most significant cost in agricultural logistics and, second, particularly sensitive to disruptions of transport, loading, and storage infrastructure, management of fuel costs is crucial to assure profit margin of an agricultural enterprise. By transforming the standard economic order quantity (EOQ) model, the authors attempt to build an approach to the optimization of fuel costs. The analysis made in the cases of twelve large crop farms in three territories of Southern Russia allowed the consideration of: (1) fragmentation in storage infrastructure; (2) variations in fuel consumption depending on the vehicle load ratio; (3) the use of their own fleet of vehicles against the outsourcing of transport operations. The authors find that the tactics of optimization of fuel costs vary depending on the location of a farm in relation to grain storage facilities. Particularly, the farms located in areas of high concentration of storage facilities benefit from using their own fleet of vehicles, while those experiencing longer distances of transportation should outsource the performance of logistics operations to third parties. To overcome a site-specific nature, the transformed EOQ model should accommodate country-specific requirements, specifically, the level of fragmentation of transport and storage infrastructure, average distance of transportation from a farm to receival site, and average fuel consumption rates depending on the types of trucks commonly used by farmers. The key recommendation is that sustainability-aimed management of logistics costs should consider combining the operation of trucks by a farm with the outsourcing of transportation operations to address the fragmentation of transport and storage infrastructure.

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“…The cost of fuel is normally the largest of all the transportation costs [9,23]. Fuel is a particularly significant cost in agriculture due to two major reasons.…”

Section: Interest On Capitalmentioning

confidence: 99%

Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm

2019

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“…Transportation and logistics companies with a vehicle fleet in goods road transportation have the aim to realize all planned transportation tasks in the observed time, simultaneously generating as low costs as possible so as to make a bigger profit. As fuel consumption for the realization of transportation tasks has a significant share in costs [1][2][3], an increase in the energy efficiency of a vehicle fleet is one of the significant measures for achieving the goal of the considered companies [4][5][6] and is yet increasingly gaining in importance when the environment is observed since road transportation has a dominant share in final energy consumption in the transportation sector [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the influence of terrain and traffic road conditions on the driver’s driving performances by applying machine learning

et al. 2022

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In this paper, research is done in the influence of different terrain and traffic conditions on road sections on the driver?s driving performances, i.e. on the car energy efficiency and CO2 emission. A methodology aimed at determining to which extent unfavorable traffic and/or terrain conditions on a road section contribute to the driver?s worse driving performances, and also to determine when the driver?s aggressive driving style is responsible for greater fuel consumption and greater CO2 emission is proposed. In order to apply the proposed methodology, a research study was carried out in a cargo transportation company and 12 drives who drove the same vehicle on five different road sections were selected. As many as 284 014 of the instances of the data about the defined parameters of the road section and the driver?s driving style were collected, based on which and with the help of machine learning a prediction of the scores for the road section and the scores for the driver?s driving style was performed. The obtained results have shown that the proposed methodology is a useful tool for managers enabling them to simply and quickly determine potential room for increasing the energy efficiency of the vehicle fleet and decreasing CO2 emission.

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Evaluation of professional driver’s eco-driving skills based on type-2 fuzzy logic model

Zdravković

Vujanovic

Stokic

et al. 2021

Neural Comput & Applic

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Optimization Method and Software for Fuel Cost Reduction in Case of Road Transport Activity

Cited by 6 publications

References 6 publications

Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm

Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm

Evaluation of the influence of terrain and traffic road conditions on the driver’s driving performances by applying machine learning

Evaluation of professional driver’s eco-driving skills based on type-2 fuzzy logic model

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