Optimize process data and final results

<div><p>In this study, the optimization of construction machinery scheduling within roadbed construction projects is explored, taking into account both personnel fatigue and sequence-dependent setup times. A sophisticated optimization model has been developed to simulate the optimal oper...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Dawei Wang (471687) (author)
مؤلفون آخرون: Bo Gao (106513) (author), Lei Zhang (38117) (author)
منشور في: 2025
الموضوعات:
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author Dawei Wang (471687)
author2 Bo Gao (106513)
Lei Zhang (38117)
author2_role author
author
author_facet Dawei Wang (471687)
Bo Gao (106513)
Lei Zhang (38117)
author_role author
dc.creator.none.fl_str_mv Dawei Wang (471687)
Bo Gao (106513)
Lei Zhang (38117)
dc.date.none.fl_str_mv 2025-05-21T21:03:31Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0320753.s001
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Optimize_process_data_and_final_results/29122805
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Molecular Biology
Plasma Physics
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
simulation outcomes confirm
promising new approach
improved gray wolf
handle constraints effectively
dependent setup times
proposed ihwgwo demonstrates
whale algorithm fused
personnel fatigue based
sophisticated optimization model
construction machinery optimization
personnel fatigue
ihwgwo ),
worker fatigue
xlink ">
significant reduction
rigorous analysis
penalty function
optimal operation
iterations required
iteration count
innovative algorithm
financial expenditure
existing algorithms
energy consumption
challenges posed
algorithm reduces
dc.title.none.fl_str_mv Optimize process data and final results
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <div><p>In this study, the optimization of construction machinery scheduling within roadbed construction projects is explored, taking into account both personnel fatigue and sequence-dependent setup times. A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. This algorithm reduces the number of iterations required for optimization and, subsequently, cuts down on energy consumption. Through rigorous analysis and comparison with existing algorithms, the proposed IHWGWO demonstrates a significant reduction in both iteration count and financial expenditure. Simulation outcomes confirm the accuracy and practicality of the model and algorithm, establishing a promising new approach for scheduling in construction engineering.</p></div>
eu_rights_str_mv openAccess
id Manara_b3abebfe86676ebc9fa5ffcfc6c78d2d
identifier_str_mv 10.1371/journal.pone.0320753.s001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/29122805
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Optimize process data and final resultsDawei Wang (471687)Bo Gao (106513)Lei Zhang (38117)Molecular BiologyPlasma PhysicsSpace ScienceBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedsimulation outcomes confirmpromising new approachimproved gray wolfhandle constraints effectivelydependent setup timesproposed ihwgwo demonstrateswhale algorithm fusedpersonnel fatigue basedsophisticated optimization modelconstruction machinery optimizationpersonnel fatigueihwgwo ),worker fatiguexlink ">significant reductionrigorous analysispenalty functionoptimal operationiterations requirediteration countinnovative algorithmfinancial expenditureexisting algorithmsenergy consumptionchallenges posedalgorithm reduces<div><p>In this study, the optimization of construction machinery scheduling within roadbed construction projects is explored, taking into account both personnel fatigue and sequence-dependent setup times. A sophisticated optimization model has been developed to simulate the optimal operation of machinery, aiming to maximize equipment utilization efficiency while addressing the challenges posed by worker fatigue. An innovative algorithm, the improved hybrid gray wolf and whale algorithm fused with a penalty function for construction machinery optimization (IHWGWO), is introduced, incorporating a penalty function to handle constraints effectively. This algorithm reduces the number of iterations required for optimization and, subsequently, cuts down on energy consumption. Through rigorous analysis and comparison with existing algorithms, the proposed IHWGWO demonstrates a significant reduction in both iteration count and financial expenditure. Simulation outcomes confirm the accuracy and practicality of the model and algorithm, establishing a promising new approach for scheduling in construction engineering.</p></div>2025-05-21T21:03:31ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0320753.s001https://figshare.com/articles/dataset/Optimize_process_data_and_final_results/29122805CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/291228052025-05-21T21:03:31Z
spellingShingle Optimize process data and final results
Dawei Wang (471687)
Molecular Biology
Plasma Physics
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
simulation outcomes confirm
promising new approach
improved gray wolf
handle constraints effectively
dependent setup times
proposed ihwgwo demonstrates
whale algorithm fused
personnel fatigue based
sophisticated optimization model
construction machinery optimization
personnel fatigue
ihwgwo ),
worker fatigue
xlink ">
significant reduction
rigorous analysis
penalty function
optimal operation
iterations required
iteration count
innovative algorithm
financial expenditure
existing algorithms
energy consumption
challenges posed
algorithm reduces
status_str publishedVersion
title Optimize process data and final results
title_full Optimize process data and final results
title_fullStr Optimize process data and final results
title_full_unstemmed Optimize process data and final results
title_short Optimize process data and final results
title_sort Optimize process data and final results
topic Molecular Biology
Plasma Physics
Space Science
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
simulation outcomes confirm
promising new approach
improved gray wolf
handle constraints effectively
dependent setup times
proposed ihwgwo demonstrates
whale algorithm fused
personnel fatigue based
sophisticated optimization model
construction machinery optimization
personnel fatigue
ihwgwo ),
worker fatigue
xlink ">
significant reduction
rigorous analysis
penalty function
optimal operation
iterations required
iteration count
innovative algorithm
financial expenditure
existing algorithms
energy consumption
challenges posed
algorithm reduces