Dynamic multi-objective optimization problem solving method for decision variable classification
The invention discloses a dynamic multi-objective optimization problem solving method based on decision variable classification, and belongs to the field of multi-objective evolution.The method comprises the steps that firstly, the influence of each decision variable on convergence and diversity in...
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creator | YANG QINGSHUAI |
description | The invention discloses a dynamic multi-objective optimization problem solving method based on decision variable classification, and belongs to the field of multi-objective evolution.The method comprises the steps that firstly, the influence of each decision variable on convergence and diversity in a new environment is analyzed, the decision variables are divided into two types through k-means clustering, and the two types are diversity-related variables and convergence-related variables; in order to improve the classification accuracy, a classification method for measuring the property of a decision variable by an included angle between a sample solution and a convergence direction is provided; besides, in order to enable a convergence optimization strategy to obtain higher accuracy, an environment change degree calculation method is provided by combining historical information in consideration of the effect of information on guiding population evolution after environment change; and finally, respectively ad |
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in order to improve the classification accuracy, a classification method for measuring the property of a decision variable by an included angle between a sample solution and a convergence direction is provided; besides, in order to enable a convergence optimization strategy to obtain higher accuracy, an environment change degree calculation method is provided by combining historical information in consideration of the effect of information on guiding population evolution after environment change; and finally, respectively ad</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</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=20230718&DB=EPODOC&CC=CN&NR=116451735A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230718&DB=EPODOC&CC=CN&NR=116451735A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>YANG QINGSHUAI</creatorcontrib><title>Dynamic multi-objective optimization problem solving method for decision variable classification</title><description>The invention discloses a dynamic multi-objective optimization problem solving method based on decision variable classification, and belongs to the field of multi-objective evolution.The method comprises the steps that firstly, the influence of each decision variable on convergence and diversity in a new environment is analyzed, the decision variables are divided into two types through k-means clustering, and the two types are diversity-related variables and convergence-related variables; in order to improve the classification accuracy, a classification method for measuring the property of a decision variable by an included angle between a sample solution and a convergence direction is provided; besides, in order to enable a convergence optimization strategy to obtain higher accuracy, an environment change degree calculation method is provided by combining historical information in consideration of the effect of information on guiding population evolution after environment change; and finally, respectively ad</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyz0OwjAMQOEuDAi4gzlAh6gUZlRATEzsxU3dYpTEURIiwen5EQdgesv3psVl93BoWYO9m8SldDfSiTOB-MSWn5hYHPggnSELUUxmN4KldJUeBgnQk-b4MRkD41uBNhgjD6y_77yYDGgiLX6dFcvD_twcS_LSUvSoyVFqm5NS61WtNlW9rf4xL2cPPoM</recordid><startdate>20230718</startdate><enddate>20230718</enddate><creator>YANG QINGSHUAI</creator><scope>EVB</scope></search><sort><creationdate>20230718</creationdate><title>Dynamic multi-objective optimization problem solving method for decision variable classification</title><author>YANG QINGSHUAI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116451735A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>YANG QINGSHUAI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>YANG QINGSHUAI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Dynamic multi-objective optimization problem solving method for decision variable classification</title><date>2023-07-18</date><risdate>2023</risdate><abstract>The invention discloses a dynamic multi-objective optimization problem solving method based on decision variable classification, and belongs to the field of multi-objective evolution.The method comprises the steps that firstly, the influence of each decision variable on convergence and diversity in a new environment is analyzed, the decision variables are divided into two types through k-means clustering, and the two types are diversity-related variables and convergence-related variables; in order to improve the classification accuracy, a classification method for measuring the property of a decision variable by an included angle between a sample solution and a convergence direction is provided; besides, in order to enable a convergence optimization strategy to obtain higher accuracy, an environment change degree calculation method is provided by combining historical information in consideration of the effect of information on guiding population evolution after environment change; and finally, respectively ad</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Dynamic multi-objective optimization problem solving method for decision variable classification |
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