{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T13:25:02Z","timestamp":1777728302426,"version":"3.51.4"},"reference-count":44,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IA"],"published-print":{"date-parts":[[2022,7,8]]},"abstract":"<jats:p>Like other custom-built machinery, elevators are charecterized by a design process which includes selection, sizing and placement of components to fit a given configuration, satisfy users\u2019 requirements and adhere to stringent normative regulations. Unlike mass-produced items, the design process needs to be repeated almost from scratch each time a new configuration is considered. Since elevators are still designed mostly manually, project engineers must engage in time-consuming and error-prone activities over and over again, leaving little to be reused from one design to the next. Computer automated design can provide a cost-effective solution as it relieves the project engineer from such burdens. However, it introduces new challenges both in terms of efficiency \u2014 the search space for solutions grows exponentially in the number of component choices \u2014 and effectiveness \u2014 the perceived quality of the final design may not be as good as in the manual process. In this paper we compare three mainstream AI techniques that can provide problem-solving capabilities inside our tool LiftCreate for automated elevator design, namely Genetic Algorithms (GAs), Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). A special-purpose heuristic search technique embedded in LiftCreate provides us with a yardstick to evaluate the solutions obtained with GAs, CP and SMT and to assess their feasibility for practical applications.<\/jats:p>","DOI":"10.3233\/ia-210132","type":"journal-article","created":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T11:10:34Z","timestamp":1657278634000},"page":"131-150","source":"Crossref","is-referenced-by-count":0,"title":["A comparison of declarative AI techniques for computer automated design of elevator systems"],"prefix":"10.1177","volume":"16","author":[{"given":"G.","family":"Cicala","sequence":"first","affiliation":[{"name":"DIBRIS, Universit\u00e0 degli Studi di Genova, Via Opera Pia, Genoa, Italy"}]},{"given":"S.","family":"Demarchi","sequence":"additional","affiliation":[{"name":"DIBRIS, Universit\u00e0 degli Studi di Genova, Via Opera Pia, Genoa, Italy"}]},{"given":"M.","family":"Menapace","sequence":"additional","affiliation":[{"name":"DIBRIS, Universit\u00e0 degli Studi di Genova, Via Opera Pia, Genoa, Italy"}]},{"given":"L.","family":"Annunziata","sequence":"additional","affiliation":[{"name":"DIBRIS, Universit\u00e0 degli Studi di Genova, Via Opera Pia, Genoa, Italy"}]},{"given":"A.","family":"Tacchella","sequence":"additional","affiliation":[{"name":"DIBRIS, Universit\u00e0 degli Studi di Genova, Via Opera Pia, Genoa, Italy"}]}],"member":"179","reference":[{"key":"10.3233\/IA-210132_ref1","first-page":"543","author":"Annunziata","year":"2017","journal-title":"European Conference on Modelling and Simulation, ECMS 2017, Budapest, Hungary"},{"key":"10.3233\/IA-210132_ref2","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1016\/j.enbuild.2015.11.033","article-title":"Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort","volume":"111","author":"Ascione","year":"2016","journal-title":"Energy and Buildings"},{"key":"10.3233\/IA-210132_ref3","doi-asserted-by":"crossref","unstructured":"Bacchus F. , GAC Via Unit Propagation, In: Proceedings of the 13th International Conference on Principles and Practice of Constraint Programming (CP-2007), (2007), pp. 133\u2013147, URL B-CP2007.pdf","DOI":"10.1007\/978-3-540-74970-7_12"},{"key":"10.3233\/IA-210132_ref5","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/978-3-319-10575-8_11","author":"Barrett","year":"2018","journal-title":"Handbook of Model Checking, Springer"},{"key":"10.3233\/IA-210132_ref6","first-page":"677","volume":"5","author":"Benavides","year":"2005","journal-title":"SEKE"},{"issue":"3","key":"10.3233\/IA-210132_ref7","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1016\/S0377-2217(98)00364-6","article-title":"Constraint satisfaction problems: Algorithms and applications","volume":"119","author":"Brailsford","year":"1999","journal-title":"European Journal of Operational Research"},{"issue":"4","key":"10.3233\/IA-210132_ref8","first-page":"301","article-title":"Defining Configuring. 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