Multiobjective Differential Evolution Algorithm Balancing Multiple Stakeholders for Low-Carbon Order Scheduling in E-Waste Recycling

Order scheduling is an important part of the e-waste recycling process, which can influence the quantity and efficiency of the recycling. With the sustainable development of e-waste recycling, low-carbon order scheduling becomes a significant and challenging reverse logistics scheduling problem. How...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:IEEE transactions on evolutionary computation Ročník 27; číslo 6; s. 1912 - 1925
Hlavní autoři: Hou, Ying, Wu, Yilin, Han, Honggui
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.12.2023
Témata:
Algorithms
Balancing
Carbon
Carbon content
Dependent variables
Electronic waste
Emissions
Evolutionary algorithms
Evolutionary computation
Multiple objective analysis
Recycling
Reverse logistics
Scheduling
Sustainable development
Time dependence
Travel time
ISSN:1089-778X, 1941-0026
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Order scheduling is an important part of the e-waste recycling process, which can influence the quantity and efficiency of the recycling. With the sustainable development of e-waste recycling, low-carbon order scheduling becomes a significant and challenging reverse logistics scheduling problem. However, it is difficult to obtain an effective low-carbon order schedule considering the conflicting interests of the multiple stakeholders, including enterprises, drivers, customers, and governments. To address this issue, a multiobjective order scheduling model (MOOSM) and a multiobjective differential evolution algorithm balancing multiple stakeholders (MODE-MS) are proposed in this article. First, to embody the interests of different stakeholders, three time-dependent key variables are calculated by the road congestion and vehicle load, including the velocity, traveling time, and carbon emission. Second, with the above key variables, a five-objective order scheduling model is formulated to describe the low-carbon order scheduling problem in e-waste recycling. Third, for solving the MOOSM, a multiobjective differential evolution algorithm based on an adaptive evolutionary search strategy is developed to obtain the low-carbon and stakeholders satisfied scheduling schemes. The experimental results validate the feasibility of MOOSM and the effectiveness of MODE-MS. By comparing with four state-of-the-art algorithms, the advantages of the proposed MODE-MS are further demonstrated in solving the low-carbon order scheduling.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2023.3237336