Logistics Distribution Path Optimization Considering Carbon Emissions and Multifuel-Type Vehicles

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Publicado en:Journal of Advanced Transportation vol. 2025 (2025)
Autor principal: Ren, Chuanxiang
Otros Autores: Lu, Li, Teng, Juan, Yin, Changchang, Li, Juntao, Ji, Haowei, Wang, Xiaoqi, Fu, Fangfang
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John Wiley & Sons, Inc.
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Acceso en línea:Citation/Abstract
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022 |a 0018-1501 
024 7 |a 10.1155/atr/6668589  |2 doi 
035 |a 3238168772 
045 2 |b d20250101  |b d20251231 
084 |a 164028  |2 nlm 
100 1 |a Ren, Chuanxiang  |u College of Transportation Shandong University of Science and Technology Qingdao Shandong, China 
245 1 |a Logistics Distribution Path Optimization Considering Carbon Emissions and Multifuel-Type Vehicles 
260 |b John Wiley & Sons, Inc.  |c 2025 
513 |a Journal Article 
520 3 |a With the development of a sustainable economy, higher requirements are put forward for logistics enterprises, which not only need to meet the requirements of profit growth but also to meet the need of sustainable development. A vehicle routing problem (VRP) optimization model considering carbon emissions and multifuel-type vehicles (VRP-CEMF) is proposed to solve the problems of air pollution and high transportation cost in the current logistics distribution. An improved genetic algorithm (IGA) is designed to solve the VRP-CEMF. The impact of carbon emissions and multifuel-type vehicles on the logistics distribution path is explored by a real example simulation. The results show that the logistics distribution path optimization considering carbon emissions and multifuel-type vehicles including hybrid electric vehicles and hydrogen-fueled vehicles can significantly reduce carbon emissions on the premise of ensuring the lowest total cost. Furthermore, the impact of carbon emissions, hydrogen fuel price, and customer demand on the logistics distribution path is discussed by sensitivity analysis. The research results of this paper provide an effective reference for enterprises to control carbon emissions in the process of logistics distribution and promote the green transformation of logistics. 
653 |a Integer programming 
653 |a Customer satisfaction 
653 |a Mathematical models 
653 |a Sensitivity analysis 
653 |a Optimization 
653 |a Genetic transformation 
653 |a Air pollution 
653 |a Environmental impact 
653 |a Operating costs 
653 |a Heuristic 
653 |a Carbon 
653 |a Energy consumption 
653 |a Emissions control 
653 |a Fuzzy logic 
653 |a Hybrid electric vehicles 
653 |a Optimization models 
653 |a Vehicles 
653 |a Mathematical programming 
653 |a Emissions 
653 |a Genetic algorithms 
653 |a Electric vehicles 
653 |a Sustainable development 
653 |a Hydrogen fuels 
653 |a Linear programming 
653 |a Algorithms 
653 |a Logistics 
653 |a Vehicle routing 
653 |a Immunoglobulin A 
653 |a Economic 
653 |a Environmental 
700 1 |a Lu, Li  |u College of Transportation Shandong University of Science and Technology Qingdao Shandong, China 
700 1 |a Teng, Juan  |u College of Transportation Shandong University of Science and Technology Qingdao Shandong, China 
700 1 |a Yin, Changchang  |u College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao Shandong, China 
700 1 |a Li, Juntao  |u School of Information Beijing Wuzi University Beijing China 
700 1 |a Ji, Haowei  |u College of Transportation Shandong University of Science and Technology Qingdao Shandong, China 
700 1 |a Wang, Xiaoqi  |u Cuilian Business School Taishan College of Science and Technology Taian Shandong, China 
700 1 |a Fu, Fangfang  |u College of Transportation Shandong University of Science and Technology Qingdao Shandong, China 
773 0 |t Journal of Advanced Transportation  |g vol. 2025 (2025) 
786 0 |d ProQuest  |t ABI/INFORM Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3238168772/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text  |u https://www.proquest.com/docview/3238168772/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3238168772/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch