Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system
The invention belongs to the related technical field of workshop scheduling, and discloses a Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system, and the method comprises the steps: constructing a machining...
Gespeichert in:
| Hauptverfasser: | , , , , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | LU ZHIBING LIU ZAIWEI LI XINYU ZHOU JINLONG WANG ZHE QIN YAN LI YUXIN CUI HANGHAO |
| description | The invention belongs to the related technical field of workshop scheduling, and discloses a Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system, and the method comprises the steps: constructing a machining workpiece task pool, a machining workpiece selection rule, a topological unit distribution rule, a collaborative worker distribution rule and an intelligent agent model, the intelligent agent model comprises a multi-layer perceptron module and a strategy module based on a Soft Actor-Critic algorithm; a multi-layer perceptron module is adopted to obtain weight vectors of the selection rules of all the machined workpieces in the current state of the workshop environment, the weight vectors are adopted to recombine the priority weights of all the workpieces in the machined workpiece task pool, and the weights of all the workpieces under the composite rules are obtained; and carrying out topological unit and collaborat |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN118863351A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN118863351A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN118863351A3</originalsourceid><addsrcrecordid>eNqNjDEOwjAQBNNQIOAP5gEpogiUNopAVDTQRxf7QgyOz_JdQPyCJ2NFPIBqpZndXWafC_Wiai0U8yZasVpFtL6nqHFEL8ohRG_9Le-A0STJNCWnNDkHHUUQ-0RlPQskIJa8Am8UmPvEMj-8KD54oJAYhLnNekAzufSqRpSBzDzhNwuO62zRg2Pc_HKVbY-Ha3PKMVCLHECjR2mbc1FU1b4sd0Vd_tP5AngFUOk</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system</title><source>esp@cenet</source><creator>LU ZHIBING ; LIU ZAIWEI ; LI XINYU ; ZHOU JINLONG ; WANG ZHE ; QIN YAN ; LI YUXIN ; CUI HANGHAO</creator><creatorcontrib>LU ZHIBING ; LIU ZAIWEI ; LI XINYU ; ZHOU JINLONG ; WANG ZHE ; QIN YAN ; LI YUXIN ; CUI HANGHAO</creatorcontrib><description>The invention belongs to the related technical field of workshop scheduling, and discloses a Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system, and the method comprises the steps: constructing a machining workpiece task pool, a machining workpiece selection rule, a topological unit distribution rule, a collaborative worker distribution rule and an intelligent agent model, the intelligent agent model comprises a multi-layer perceptron module and a strategy module based on a Soft Actor-Critic algorithm; a multi-layer perceptron module is adopted to obtain weight vectors of the selection rules of all the machined workpieces in the current state of the workshop environment, the weight vectors are adopted to recombine the priority weights of all the workpieces in the machined workpiece task pool, and the weights of all the workpieces under the composite rules are obtained; and carrying out topological unit and collaborat</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20241029&DB=EPODOC&CC=CN&NR=118863351A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25544,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20241029&DB=EPODOC&CC=CN&NR=118863351A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LU ZHIBING</creatorcontrib><creatorcontrib>LIU ZAIWEI</creatorcontrib><creatorcontrib>LI XINYU</creatorcontrib><creatorcontrib>ZHOU JINLONG</creatorcontrib><creatorcontrib>WANG ZHE</creatorcontrib><creatorcontrib>QIN YAN</creatorcontrib><creatorcontrib>LI YUXIN</creatorcontrib><creatorcontrib>CUI HANGHAO</creatorcontrib><title>Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system</title><description>The invention belongs to the related technical field of workshop scheduling, and discloses a Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system, and the method comprises the steps: constructing a machining workpiece task pool, a machining workpiece selection rule, a topological unit distribution rule, a collaborative worker distribution rule and an intelligent agent model, the intelligent agent model comprises a multi-layer perceptron module and a strategy module based on a Soft Actor-Critic algorithm; a multi-layer perceptron module is adopted to obtain weight vectors of the selection rules of all the machined workpieces in the current state of the workshop environment, the weight vectors are adopted to recombine the priority weights of all the workpieces in the machined workpiece task pool, and the weights of all the workpieces under the composite rules are obtained; and carrying out topological unit and collaborat</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNjDEOwjAQBNNQIOAP5gEpogiUNopAVDTQRxf7QgyOz_JdQPyCJ2NFPIBqpZndXWafC_Wiai0U8yZasVpFtL6nqHFEL8ohRG_9Le-A0STJNCWnNDkHHUUQ-0RlPQskIJa8Am8UmPvEMj-8KD54oJAYhLnNekAzufSqRpSBzDzhNwuO62zRg2Pc_HKVbY-Ha3PKMVCLHECjR2mbc1FU1b4sd0Vd_tP5AngFUOk</recordid><startdate>20241029</startdate><enddate>20241029</enddate><creator>LU ZHIBING</creator><creator>LIU ZAIWEI</creator><creator>LI XINYU</creator><creator>ZHOU JINLONG</creator><creator>WANG ZHE</creator><creator>QIN YAN</creator><creator>LI YUXIN</creator><creator>CUI HANGHAO</creator><scope>EVB</scope></search><sort><creationdate>20241029</creationdate><title>Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system</title><author>LU ZHIBING ; LIU ZAIWEI ; LI XINYU ; ZHOU JINLONG ; WANG ZHE ; QIN YAN ; LI YUXIN ; CUI HANGHAO</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN118863351A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>LU ZHIBING</creatorcontrib><creatorcontrib>LIU ZAIWEI</creatorcontrib><creatorcontrib>LI XINYU</creatorcontrib><creatorcontrib>ZHOU JINLONG</creatorcontrib><creatorcontrib>WANG ZHE</creatorcontrib><creatorcontrib>QIN YAN</creatorcontrib><creatorcontrib>LI YUXIN</creatorcontrib><creatorcontrib>CUI HANGHAO</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LU ZHIBING</au><au>LIU ZAIWEI</au><au>LI XINYU</au><au>ZHOU JINLONG</au><au>WANG ZHE</au><au>QIN YAN</au><au>LI YUXIN</au><au>CUI HANGHAO</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system</title><date>2024-10-29</date><risdate>2024</risdate><abstract>The invention belongs to the related technical field of workshop scheduling, and discloses a Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system, and the method comprises the steps: constructing a machining workpiece task pool, a machining workpiece selection rule, a topological unit distribution rule, a collaborative worker distribution rule and an intelligent agent model, the intelligent agent model comprises a multi-layer perceptron module and a strategy module based on a Soft Actor-Critic algorithm; a multi-layer perceptron module is adopted to obtain weight vectors of the selection rules of all the machined workpieces in the current state of the workshop environment, the weight vectors are adopted to recombine the priority weights of all the workpieces in the machined workpiece task pool, and the weights of all the workpieces under the composite rules are obtained; and carrying out topological unit and collaborat</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN118863351A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Soft Actor-Critic reinforcement learning-based resource collaborative installation and adjustment workshop adaptive scheduling method and system |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-27T14%3A12%3A15IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=LU%20ZHIBING&rft.date=2024-10-29&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN118863351A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |