Production line scheduling method based on data and model hybrid drive
The invention discloses a production line scheduling method based on data and model hybrid drive, and the method comprises the steps: constructing a flexible production line scheduling model under random disturbance according to the resource position and layout, the number and type of operation orde...
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| creator | CHEN JIE WANG GANG ZHANG SHAOQING GAN MINGGANG ZHU YIBING MA QIANZHAO XIA MINGYUE |
| description | The invention discloses a production line scheduling method based on data and model hybrid drive, and the method comprises the steps: constructing a flexible production line scheduling model under random disturbance according to the resource position and layout, the number and type of operation orders, random noise disturbance and other elements in a flexible production line; then, according to a data and model hybrid driving framework, solving the scheduling model; in a data and model hybrid driving framework, data driving refers to a value decomposition-based multi-agent reinforcement learning algorithm, model driving refers to a heuristic assignment rule and experience knowledge, and hybrid driving of the data driving and the model driving is mainly reflected in three aspects: firstly, the scheduling rule is used for guiding agent strategy selection; secondly, designing a reward function based on scheduling scene knowledge; thirdly, training a noise detection and denoising module by using historical experi |
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then, according to a data and model hybrid driving framework, solving the scheduling model; in a data and model hybrid driving framework, data driving refers to a value decomposition-based multi-agent reinforcement learning algorithm, model driving refers to a heuristic assignment rule and experience knowledge, and hybrid driving of the data driving and the model driving is mainly reflected in three aspects: firstly, the scheduling rule is used for guiding agent strategy selection; secondly, designing a reward function based on scheduling scene knowledge; thirdly, training a noise detection and denoising module by using historical experi</description><language>chi ; eng</language><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL ; CONTROLLING ; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS ; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS ; PHYSICS ; REGULATING</subject><creationdate>2023</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=20230908&DB=EPODOC&CC=CN&NR=116719285A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230908&DB=EPODOC&CC=CN&NR=116719285A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>CHEN JIE</creatorcontrib><creatorcontrib>WANG GANG</creatorcontrib><creatorcontrib>ZHANG SHAOQING</creatorcontrib><creatorcontrib>GAN MINGGANG</creatorcontrib><creatorcontrib>ZHU YIBING</creatorcontrib><creatorcontrib>MA QIANZHAO</creatorcontrib><creatorcontrib>XIA MINGYUE</creatorcontrib><title>Production line scheduling method based on data and model hybrid drive</title><description>The invention discloses a production line scheduling method based on data and model hybrid drive, and the method comprises the steps: constructing a flexible production line scheduling model under random disturbance according to the resource position and layout, the number and type of operation orders, random noise disturbance and other elements in a flexible production line; then, according to a data and model hybrid driving framework, solving the scheduling model; in a data and model hybrid driving framework, data driving refers to a value decomposition-based multi-agent reinforcement learning algorithm, model driving refers to a heuristic assignment rule and experience knowledge, and hybrid driving of the data driving and the model driving is mainly reflected in three aspects: firstly, the scheduling rule is used for guiding agent strategy selection; secondly, designing a reward function based on scheduling scene knowledge; thirdly, training a noise detection and denoising module by using historical experi</description><subject>CONTROL OR REGULATING SYSTEMS IN GENERAL</subject><subject>CONTROLLING</subject><subject>FUNCTIONAL ELEMENTS OF SUCH SYSTEMS</subject><subject>MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS</subject><subject>PHYSICS</subject><subject>REGULATING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHALKMpPKU0uyczPU8jJzEtVKE7OSE0pBTLTFXJTSzLyUxSSEotTUxSA8imJJYkKiXkpCrn5Kak5ChmVSUWZKQopRZllqTwMrGmJOcWpvFCam0HRzTXE2UM3tSA_PrW4IDE5NS-1JN7Zz9DQzNzQ0sjC1NGYGDUAEtMzSQ</recordid><startdate>20230908</startdate><enddate>20230908</enddate><creator>CHEN JIE</creator><creator>WANG GANG</creator><creator>ZHANG SHAOQING</creator><creator>GAN MINGGANG</creator><creator>ZHU YIBING</creator><creator>MA QIANZHAO</creator><creator>XIA MINGYUE</creator><scope>EVB</scope></search><sort><creationdate>20230908</creationdate><title>Production line scheduling method based on data and model hybrid drive</title><author>CHEN JIE ; 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| subjects | CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING FUNCTIONAL ELEMENTS OF SUCH SYSTEMS MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING |
| title | Production line scheduling method based on data and model hybrid drive |
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