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  "author": "Clemens H\u00fcbler, Benedikt Hofmeister",
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  "author": "Clemens H\u00fcbler, Benedikt Hofmeister",
            
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  "author_email": "c.huebler@isd.uni-hannover.de",
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  "author_email": "c.huebler@isd.uni-hannover.de",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/0043276",
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  "doi": "10.25835/0043276",
            
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  "doi_date_published": "2020-12-08",
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  "doi_date_published": "2020-12-08",
            
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  "doi_publisher": "LUIS",
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  "doi_publisher": "LUIS",
            
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  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
            
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  "have_copyright": "Yes",
            
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  "license_id": "CC-BY-SA-3.0",
            
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  "license_title": "CC-BY-SA-3.0",
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  "license_title": "CC-BY-SA-3.0",
            
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  "maintainer": "Clemens H\u00fcbler",
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  "maintainer": "Clemens H\u00fcbler",
            
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  "maintainer_email": "c.huebler@isd.uni-hannover.de",
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  "maintainer_email": "c.huebler@isd.uni-hannover.de",
            
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  "name": "luh-global-pattern-search-for-alpha-level-optimisation",
            
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  "notes": "The Global Pattern Search for alpha-level Optimisation 
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  "notes": "The Global Pattern Search for alpha-level Optimisation 
            
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(aGPS) is a global optimisation approach explicitly designed for 
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(aGPS) is a global optimisation approach explicitly designed for 
            
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efficient and user-friendly alpha-level optimisations. It can be used 
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efficient and user-friendly alpha-level optimisations. It can be used 
            
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to improve the efficiency of fuzzy structural analyses. The  
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to improve the efficiency of fuzzy structural analyses. The  
            
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efficiency of aGPS stems from its deterministic sample generation, 
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efficiency of aGPS stems from its deterministic sample generation, 
            
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which allows a reuse of many samples within the various alpha-level 
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which allows a reuse of many samples within the various alpha-level 
            
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optimisations. Moreover, information gained within an alpha-level 
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optimisations. Moreover, information gained within an alpha-level 
            
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optimisation is used for all subsequent optimisations. It outperforms 
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optimisation is used for all subsequent optimisations. It outperforms 
            
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state-of-the-art algorithms. This means that it requires less model 
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state-of-the-art algorithms. This means that it requires less model 
            
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evaluations, and therefore, it has lower computing times. \r\nHere, 
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evaluations, and therefore, it has lower computing times. \r\nHere, 
            
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the entire source code for its implementation in MATLAB is given. 
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the entire source code for its implementation in MATLAB is given. 
            
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\r\nFor further information, it is referred to \"Huebler, C., & 
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\r\nFor further information, it is referred to \"Huebler, C., & 
            
n
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Hofmeister, R. (2021). Efficient and user-friendly alpha-level 
n
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Hofmeister, B. (2021). Efficient and user-friendly alpha-level 
            
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optimisation for application-orientated fuzzy structural analyses. 
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optimisation for application-orientated fuzzy structural analyses. 
            
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Submitted to Engineering Structures.\"",
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Submitted to Engineering Structures.\"",
            
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    "description": "(Institute of Structural Analysis) 
            
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Appelstra\u00dfe 9A 30167 Hannover 
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Appelstra\u00dfe 9A 30167 Hannover 
            
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(Germany)\r\n\r\nhttps://www.isd.uni-hannover.de/en/institute/",
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(Germany)\r\n\r\nhttps://www.isd.uni-hannover.de/en/institute/",
            
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