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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| مؤلفون آخرون: | , |
| منشور في: |
2025
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| _version_ | 1852020160070680576 |
|---|---|
| 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 |