CAS OpenIR
Novel approach to energy-efficient flexible job-shop scheduling problems
Rakovitis, Nikolaos1; Li, Dan1; Zhang, Nan1; Li, Jie1; Zhang, Liping2; Xiao, Xin3
2022
Source PublicationENERGY
ISSN0360-5442
Volume238Pages:16
AbstractIn this work, we develop a novel mathematical formulation for the energy-efficient flexible job-shop scheduling problem using the improved unit-specific event-based time representation. The flexible job-shop is represented using the state-task network. It is shown that the proposed model is superior to the existing models with the same or better solutions by up to 13.5 % energy savings in less computational time. Furthermore, it can generate feasible solutions for large-scale instances that the existing models fail to solve. To efficiently solve large-scale problems, a grouping-based decomposition approach is proposed to divide the entire problem into smaller subproblems. It is demonstrated that the proposed decomposition approach can generate good feasible solutions with reduced energy consumption for large-scale examples in significantly less computational time (within 10 min). It can achieve up to 43.1 % less energy consumption in comparison to the existing gene-expression programming-based algorithm. (c) 2021 Elsevier Ltd. All rights reserved.
KeywordScheduling Mixed-integer programming Flexible job-shops Energy-efficient Unit-specific event-based
DOI10.1016/j.energy.2021.121773
Language英语
WOS KeywordMULTIOBJECTIVE OPTIMIZATION ; MATHEMATICAL-MODELS ; SHORT-TERM ; ALGORITHM ; TRANSPORTATION ; OPERATIONS
Funding ProjectUniversity of Manchester ; China Scholarship Council-The University of Manchester Joint Scholarship[201908130170] ; National Natural Science Foundation of China[51875420] ; Engineering and Physical Sciences Research Council[EP/T03145X/1]
WOS Research AreaThermodynamics ; Energy & Fuels
WOS SubjectThermodynamics ; Energy & Fuels
Funding OrganizationUniversity of Manchester ; China Scholarship Council-The University of Manchester Joint Scholarship ; National Natural Science Foundation of China ; Engineering and Physical Sciences Research Council
WOS IDWOS:000701940800003
PublisherPERGAMON-ELSEVIER SCIENCE LTD
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Document Type期刊论文
Identifierhttp://ir.ipe.ac.cn/handle/122111/50426
Collection中国科学院过程工程研究所
Corresponding AuthorLi, Jie
Affiliation1.Univ Manchester, Ctr Proc Integrat, Dept Chem Engn & Analyt Sci, Manchester M13 9PL, Lancs, England
2.Wuhan Univ Sci & Technol, Sch Machinery & Automat, Dept Ind Engn, Wuhan 430081, Hubei, Peoples R China
3.Chinese Acad Sci, Inst Proc Engn, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Rakovitis, Nikolaos,Li, Dan,Zhang, Nan,et al. Novel approach to energy-efficient flexible job-shop scheduling problems[J]. ENERGY,2022,238:16.
APA Rakovitis, Nikolaos,Li, Dan,Zhang, Nan,Li, Jie,Zhang, Liping,&Xiao, Xin.(2022).Novel approach to energy-efficient flexible job-shop scheduling problems.ENERGY,238,16.
MLA Rakovitis, Nikolaos,et al."Novel approach to energy-efficient flexible job-shop scheduling problems".ENERGY 238(2022):16.
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