Optimization of agricultural biomass Supply: Dual reduction of cost and carbon emissions based on multi-objective arithmetic optimization algorithm

Energy serves as a crucial foundation for the development of human society, yet the limited availability of fossil fuels and their environmental impact constrain sustainable progress. Against the backdrop of “carbon peaking and carbon neutrality,” agricultural biomass, as a vital renewable energy so...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of cleaner production Jg. 511; S. 145670
Hauptverfasser: Li, Pengfei, Liang, Jialiang, Xue, Ye, Tan, Shizheng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 15.06.2025
Schlagworte:
Agricultural biomass
algorithms
arithmetics
biofuels
biomass
carbon
carbon dioxide
Carbon emissions
Economic cost
energy
environmental impact
environmental sustainability
humans
mathematical models
Multi-objective arithmetic optimization algorithm
prices
Sensitivity analysis
supply chain
Supply optimization
transportation
Multi-objective arithmetic optimization algorithm
Sensitivity analysis
Supply optimization
Agricultural biomass
Carbon emissions
Economic cost
ISSN:0959-6526
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Energy serves as a crucial foundation for the development of human society, yet the limited availability of fossil fuels and their environmental impact constrain sustainable progress. Against the backdrop of “carbon peaking and carbon neutrality,” agricultural biomass, as a vital renewable energy source, plays a key role in achieving economic and environmental sustainability through the rational allocation of supply quantities at storage points. This study focuses on the agricultural biomass supply chain and establishes a mathematical model encompassing three stages: field collection, storage, transportation, and the supply of solid biofuels. Using a multi-objective arithmetic optimization algorithm, the model aims to minimize economic costs and carbon emissions by optimizing supply allocations at storage points. Based on field data analysis from emerging biofuel enterprises, the optimized solution reduces total economic costs by 6.91 % (2.92 million yuan) and carbon emissions by 8.08 % (388.51 tons of CO2). Specific adjustments show a 64.72 % reduction in the supply from Lankao County, with increases of 67.16 % and 186.82 % in Bo'ai County and Linying County, respectively. Further analysis reveals that procurement and processing of agricultural biomass are the primary sources of economic costs, while carbon emissions mainly originate from the processing phase and long-distance transportation. Sensitivity analysis highlights the critical roles of key parameters, particularly the purchase price of biomass and the unit cost of processing and maintenance of solid biofuels, in influencing total costs. Similarly, the carbon emissions from biofuel processing and the transport capacity of large trucks are identified as pivotal factors affecting overall emissions. [Display omitted] •Developed model for biomass collection, storage, transportation, and supply.•MOAOA was introduced to optimize the supply quantities at three storage points.•The optimization plan reduced the company's economic costs and carbon emissions.•Provided a practical pathway for China's carbon peak and neutrality goals.•Promoted innovative applications of MOAOA in the agricultural biomass supply process.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0959-6526
DOI:10.1016/j.jclepro.2025.145670