{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T17:48:29Z","timestamp":1763747309154},"reference-count":32,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2014,7,22]],"date-time":"2014-07-22T00:00:00Z","timestamp":1405987200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[2014,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The use of generative design grammars for computational design synthesis has been shown to be successful in many application areas. The development of advanced search and optimization strategies to guide the computational synthesis process is an active research area with great improvements in the last decades. The development of the grammar rules, however, often resembles an art rather than a science. Poor grammars drive the need for problem specific and sophisticated search and optimization algorithms that guide the synthesis process toward valid and optimized designs in a reasonable amount of time. Instead of tuning search algorithms for inferior grammars, this research focuses on designing better grammars to not unnecessarily burden the search process. It presents a grammar rule analysis method to provide a more systematic development process for grammar rules. The goal of the grammar rule analysis method is to improve the quality of the rules and in turn have a major impact on the quality of the designs generated. Four different grammars for automated gearbox synthesis are used as a case study to validate the developed method and show its potential.<\/jats:p>","DOI":"10.1017\/s0890060414000195","type":"journal-article","created":{"date-parts":[[2014,7,22]],"date-time":"2014-07-22T08:26:21Z","timestamp":1406017581000},"page":"227-238","source":"Crossref","is-referenced-by-count":14,"title":["Systematic rule analysis of generative design grammars"],"prefix":"10.1017","volume":"28","author":[{"given":"Corinna","family":"K\u00f6nigseder","sequence":"first","affiliation":[]},{"given":"Kristina","family":"Shea","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2014,7,22]]},"reference":[{"key":"S0890060414000195_ref3","doi-asserted-by":"publisher","DOI":"10.1115\/1.2013289"},{"key":"S0890060414000195_ref32","doi-asserted-by":"crossref","unstructured":"Zheng L. , & Chen H. (2009). A systematic framework for grammar testing. Proc. 8th IEEE\/ACIS Int. Conf. Computer and Information Science, Shanghai, June 1\u20133.","DOI":"10.1109\/ICIS.2009.193"},{"key":"S0890060414000195_ref12","unstructured":"Klein D. , & Manning C.D. (2002). A generative constituent-context model for improved grammar induction. 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(2008 a). Automating the creation of shape grammar rules. Proc. Design Computing and Cognition \u201808, 3\u201322.","DOI":"10.1007\/978-1-4020-8728-8_1"},{"key":"S0890060414000195_ref15","volume-title":"Proc. Artificial Intelligence in Design \u201898","author":"Knight","year":"1998"},{"key":"S0890060414000195_ref10","doi-asserted-by":"publisher","DOI":"10.1115\/1.4005592"},{"key":"S0890060414000195_ref8","volume-title":"Proc. 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