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Designing is a problem-solving activity. The process is usually iterative: a solution is proposed, then analysed and tested until it satisfies all constraints and best fulfils the criteria. Usually, a designer proposes a solution based on intuition, experience, and knowledge. However, this does not work for problems they are facing for the first time. An alternative approach is generative design, where the designer focuses on iteratively defining a problem with its constraints and criteria in the form of a parametric computational model, and then leaves the search for the solution to the algorithms and their ability to rapidly generate and test several alternatives. The result of this approach is not only a set of solutions embedding implicitly the knowledge but also a model where problem-defining knowledge is quite explicit. The idea of the proposed approach is the exploitation of synergies between the designer and the algorithms. The designer focuses on problem definition and the algorithm focuses on finding a solution, showing that the capacity of the generative approach to replace the designer is limited. In the paper, we first present the framework of generative design, then apply the process to a case study of designing an efficient shading solution, and in the end, we present the results and compare them with the traditional approach. The approach is general and can be applied in other areas of engineering. It is relevant both to designers as well as software developers who are expected to take this approach further. More theoretical work is needed to study problem definitions as a form of knowledge representation in engineering. Oblikovanje je dejavnost reševanja problemov. Postopek je ponavadi iterativen: predlaga se rešitev, ki se nato analizira in preizkuša, dokler ne zadosti vsem omejitvam in najbolje izpolnjuje merila. Običajno projektant predlaga rešitev na podlagi intuicije, izkušenj in znanja. Vendar pa to ne deluje pri problemih, s katerimi se srečujejo prvič. Alternativni pristop je generativno načrtovanje, pri katerem se projektant osredotoči na iterativno opredelitev problema z njegovimi omejitvami in merili v obliki parametričnega računalniškega modela, nato pa iskanje rešitve prepusti algoritmom in njihovi zmožnosti hitrega generiranja in testiranja več alternativ. Rezultat tega pristopa ni le nabor rešitev, ki implicitno vključujejo znanje, temveč tudi model, v katerem je znanje o opredelitvi problema precej eksplicitno. Ideja predlaganega pristopa je izkoriščanje sinergij med oblikovalcem in algoritmi. Projektant se osredotoča na opredelitev problema, algoritem pa na iskanje rešitve, kar kaže, da je zmožnost generativnega pristopa, da nadomesti projektanta, omejena. V članku najprej predstavimo okvir generativnega načrtovanja, nato postopek uporabimo za študijo primera načrtovanja učinkovite rešitve senčenja, na koncu pa predstavimo rezultate in jih primerjamo s tradicionalnim pristopom. Pristop je splošen in se lahko uporablja tudi na drugih področjih inženirstva. Pomemben je tako za projektante kot tudi za razvijalce programske opreme, od katerih se pričakuje, da bodo ta pristop razvijali naprej. Potrebno je več teoretičnega dela za preučevanje opredelitev problemov kot oblike predstavitve znanja v inženirstvu.

The construction industry suffers from the lack of adoption of advanced technologies. As a consequence, construction is among the least productive industries across various sectors. The researchers often point out that the critical issue is the lack of integration throughout the building project life cycle. Lack of information integration causes reworks unexpected changes, lower construction quality, delays, and on-site conflicts, which could be addressed in advance by a proper constructability study executed already in the design phase. Constructability is a technique that examines the logic of construction from the beginning to the end, seeking technical solutions that reduce project cost, time, and waste. The central part of the thesis provides a comprehensive overview and analysis of non-technical and technical constructability issues. Special attention is given to Lean and BIM approaches, which may serve as driving mechanisms that substantially improve constructability. The presented work tries to identify the value and integration of mechanisms for the improvement of constructability issues. Among the technical issues, the rationalization of the design plays an essential role in improving the execution and reducing project costs and delays. The final part of the thesis focuses on the rationalization of design addressing constructability issues by employing Generative Design. This approach is demonstrated in a case study of a complex building –Stožice Arena. The Arena case study shows the design rationalization techniques using generative design and machine learning, enabling informed shaping and clustering of the building envelope. The presented solution contributes to the evolving field of future architectural-structural design methods. Gradbena industrija zaostaja pri uvajanju sodobnih tehnologij, zaradi česar gradbeništvo sodi med najbolj neučinkovite industrije z eno najnižjih stopenj produktivnosti med sektorji. Osrednji vidik, ki vpliva na nastalo stanje, je pomanjkanje integracije skozi življenjski cikel gradbenega projekta. Pomanjkanje integracije povzroča ponovno delo na posameznih projektih, brez da bi temeljito preučili zahteve za izvedljivost gradbenih del. Študija izvedljivosti gradbenih del je tehnika, ki sistematično preučuje logiko gradbenih del od začetka do konca, s ciljem, da zniža stroške, potreben čas za izvedbo in količino odpadnega materiala projekta. Vitka proizvodnja in BIM sta mehanizma, ki podpirata proces, ki je nujen, če želimo izboljšati izvedljivost gradbenih del. Pričujoča disertacija integrira te mehanizme, na način, da najprej identificiramo vrednost mehanizmov za reševanje najbolj pogostih težav pri izvedbi gradbenih del in jih nato vgradimo v študije izvedljivosti gradbenih del v fazi načrtovanja. Poleg tega naloga tudi obravnava, kako bi lahko z uporabo vitke proizvodnje in BIM odpravili ne-tehnične težave. Med tehničnimi težavami ima racionalizacija načrtovalskih rešitev ključen pomen pri izboljšanju izvedbe in zmanjšanju stroškov. Pristop je prikazan na študiji primera Arene Stožice, kjer je prikazana optimizacija oblike z uporabo orodij za generativno načrtovanje, ki omogoča iskanje optimalnih načrtovalskih rešitev. V sklepnem delu študije prikažemo tudi uporabnost strojnega učenja za standardizacijo in združevanje konstrukcijskih sistemov fasadnega ovoja.