A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs
This paper presents a new Pareto-based coordinate exchange algorithm for populating or approximating the true Pareto front for multi-criteria optimal experimental design problems that arise naturally in a range of industrial applications. This heuristic combines an elitist-like operator inspired by...
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| Veröffentlicht in: | Statistics and computing 2017-03, Vol.27 (2), p.423-437 |
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| container_title | Statistics and computing |
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| creator | Cao, Yongtao Smucker, Byran J. Robinson, Timothy J. |
| description | This paper presents a new Pareto-based coordinate exchange algorithm for populating or approximating the true Pareto front for multi-criteria optimal experimental design problems that arise naturally in a range of industrial applications. This heuristic combines an elitist-like operator inspired by evolutionary multi-objective optimization algorithms with a coordinate exchange operator that is commonly used to construct optimal designs. Benchmarking results from both a two-dimensional and three-dimensional example demonstrate that the proposed hybrid algorithm can generate highly reliable Pareto fronts with less computational effort than existing procedures in the statistics literature. The proposed algorithm also utilizes a multi-start operator, which makes it readily parallelizable for high performance computing infrastructures. |
| doi_str_mv | 10.1007/s11222-016-9630-9 |
| format | Article |
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This heuristic combines an elitist-like operator inspired by evolutionary multi-objective optimization algorithms with a coordinate exchange operator that is commonly used to construct optimal designs. Benchmarking results from both a two-dimensional and three-dimensional example demonstrate that the proposed hybrid algorithm can generate highly reliable Pareto fronts with less computational effort than existing procedures in the statistics literature. The proposed algorithm also utilizes a multi-start operator, which makes it readily parallelizable for high performance computing infrastructures.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Design of experiments</subject><subject>Elitism</subject><subject>Evolutionary algorithms</subject><subject>Exchanging</subject><subject>Industrial applications</subject><subject>Mathematics and Statistics</subject><subject>Multiple criterion</subject><subject>Multiple objective analysis</subject><subject>Pareto optimization</subject><subject>Probability and Statistics in Computer Science</subject><subject>Statistical Theory and Methods</subject><subject>Statistics</subject><subject>Statistics and Computing/Statistics Programs</subject><issn>0960-3174</issn><issn>1573-1375</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LAzEQhoMoWD9-gLeA5-jMJt3sHkvxCwQveg5pdrZN2W7WJIX6743UgxcvMwzzvu8MD2M3CHcIoO8TYlVVArAWbS1BtCdshnMtBUo9P2UzaGsQErU6ZxcpbQEQa6lm7LDgm69V9B2nwWefMp9spBzEyibquAshdn60mTgd3MaOa-J2WIfo82bH-xCLYkw57l3245rv9kP2wpUtRW95mLLf2aFYpzLvaMxl6Cj59Ziu2Flvh0TXv_2SfTw-vC-fxevb08ty8SqcxDqLSoMCWREi6t7OlZRareS8FAW2UW0rXd9ZUq6u66YDTQ2SBmotOLSrXslLdnvMnWL43FPKZhv2cSwnDTYN6FZqaIoKjyoXQ0qRejOVh238MgjmB7A5AjYFsPkBbNriqY6eVLQFTPyT_K_pGxQbgA8</recordid><startdate>20170301</startdate><enddate>20170301</enddate><creator>Cao, Yongtao</creator><creator>Smucker, Byran J.</creator><creator>Robinson, Timothy J.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20170301</creationdate><title>A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs</title><author>Cao, Yongtao ; Smucker, Byran J. ; Robinson, Timothy J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-2704032e1117fa543374b3574b40a84993cfdae4c6668d07e81e70e9a0c1abf43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Design of experiments</topic><topic>Elitism</topic><topic>Evolutionary algorithms</topic><topic>Exchanging</topic><topic>Industrial applications</topic><topic>Mathematics and Statistics</topic><topic>Multiple criterion</topic><topic>Multiple objective analysis</topic><topic>Pareto optimization</topic><topic>Probability and Statistics in Computer Science</topic><topic>Statistical Theory and Methods</topic><topic>Statistics</topic><topic>Statistics and Computing/Statistics Programs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Yongtao</creatorcontrib><creatorcontrib>Smucker, Byran J.</creatorcontrib><creatorcontrib>Robinson, Timothy J.</creatorcontrib><collection>CrossRef</collection><jtitle>Statistics and computing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Yongtao</au><au>Smucker, Byran J.</au><au>Robinson, Timothy J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs</atitle><jtitle>Statistics and computing</jtitle><stitle>Stat Comput</stitle><date>2017-03-01</date><risdate>2017</risdate><volume>27</volume><issue>2</issue><spage>423</spage><epage>437</epage><pages>423-437</pages><issn>0960-3174</issn><eissn>1573-1375</eissn><abstract>This paper presents a new Pareto-based coordinate exchange algorithm for populating or approximating the true Pareto front for multi-criteria optimal experimental design problems that arise naturally in a range of industrial applications. 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| language | eng |
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| subjects | Algorithms Artificial Intelligence Design of experiments Elitism Evolutionary algorithms Exchanging Industrial applications Mathematics and Statistics Multiple criterion Multiple objective analysis Pareto optimization Probability and Statistics in Computer Science Statistical Theory and Methods Statistics Statistics and Computing/Statistics Programs |
| title | A hybrid elitist pareto-based coordinate exchange algorithm for constructing multi-criteria optimal experimental designs |
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