A bi-level multi-objective optimization approach for carbon policy formulation towards food waste resource treatment from environmental, energy and economic perspectives

Excessive food waste contributes to the greenhouse effect. Although low-carbon technology has the potential to reduce carbon emissions and generate renewable energy, the high costs may deter the adoption. To promote low-carbon food waste treatment, local authorities could develop carbon reduction policies targeted at the food waste treatment industry, which could lead to a game between local authorities and food waste treatment enterprises. Hence, a bi-level multi-objective optimization model is put forward to balance the decisions of local authorities and those of food waste treatment enterprises. Enterprises can choose which carbon reduction policies to implement, and local authorities determine the intensity of specific policies. After testing this model on Shenzhen’s food waste treatment system, the model’s validity and feasibility were confirmed. It was discovered that by identifying suitable carbon reduction policies, the model can help enterprises achieve more than 50 % carbon reduction. Moreover, different enterprises may choose different carbon reduction policies to implement. Optimal food waste disposal arrangements need flexible adjustments. The constructed model can serve as a decision-making tool for city managers to reduce carbon emissions in food waste treatment.

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Publication Details

Journal
Sustainable Futures
Published
2024-09-19
DOI
https://doi.org/10.1016/j.sftr.2024.100310
Citations
3
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
0.88
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article

A bi-level multi-objective optimization approach for carbon policy formulation towards food waste resource treatment from environmental, energy and economic perspectives

Yawen Deng, Liying Liu, Mingliang Tan, Yaqi Wang
3 citations
Sustainable Futures
Municipal Solid Waste Management
0.88
article

A bi-level multi-objective optimization approach for carbon policy formulation towards food waste resource treatment from environmental, energy and economic perspectives

Yawen Deng, Liying Liu, Mingliang Tan, Yaqi Wang
article en
3 citations

Abstract

Excessive food waste contributes to the greenhouse effect. Although low-carbon technology has the potential to reduce carbon emissions and generate renewable energy, the high costs may deter the adoption. To promote low-carbon food waste treatment, local authorities could develop carbon reduction policies targeted at the food waste treatment industry, which could lead to a game between local authorities and food waste treatment enterprises. Hence, a bi-level multi-objective optimization model is put forward to balance the decisions of local authorities and those of food waste treatment enterprises. Enterprises can choose which carbon reduction policies to implement, and local authorities determine the intensity of specific policies. After testing this model on Shenzhen’s food waste treatment system, the model’s validity and feasibility were confirmed. It was discovered that by identifying suitable carbon reduction policies, the model can help enterprises achieve more than 50 % carbon reduction. Moreover, different enterprises may choose different carbon reduction policies to implement. Optimal food waste disposal arrangements need flexible adjustments. The constructed model can serve as a decision-making tool for city managers to reduce carbon emissions in food waste treatment.

Sustainable FuturesVol. 8
North Sichuan Medical University (CN), Sichuan University (CN)
Zero hunger
Openalex Percentile: Top 25%
Municipal Solid Waste Management
0.88
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A bi-level multi-objective optimization approach for carbon policy formulation towards food waste resource treatment from environmental, energy and economic perspectives — Yawen Deng, Liying Liu, et al. · Sustainable Futures (2024) | TGRS Research Map | TGRS