Abstract Design has always played an important role in building projects, as it affects the construction process. Selecting competent design teams is a key factor that needs to be considered for the successful completion of a design project. Applying only the limited experience and subjective judgment of humans can have a negative effect on the process of decision-making, since it is difficult to sufficiently consider all the influential factors affecting the options for a combination of teams. Therefore, it is necessary to develop an automated model to effectively support experiences and judgments of decision-makers. In this context, this paper employs Case Base Reasoning(CBR) based on the solutions of similar past cases along with Genetic Algorithm(GA) generating useful solutions through combinations of each individual. The CBR-Genetic Algorithm based design team selection model used for selecting appropriate design teams was developed in this study based on a literature review and an analysis of current selection processes. The developed CBR-Genetic Algorithm based design team selection model, which consists of Modules I and II, was then validated by comparing the results obtained from twelve experts with the results that were automatically selected by Module I and II through real case studies (50 multi-family completed apartment design projects). It was shown that the CBR-Genetic Algorithm based design team selection model is superior to current selection processes because it is able to select appropriate design teams tailored for a future project by simultaneously considering numerous criteria and a variety of combinations of design team possibilities.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    CBR-genetic algorithm based design team selection model for large-scale design firms


    Beteiligte:
    Park, Sung-Chul (Autor:in) / Koo, Kyo-Jin (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2011-09-01


    Format / Umfang :

    8 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Genetic Algorithm Selection for Ship Concept Design

    Sobey, Adam / Grudniewski, Przemyslaw / Savasta, Thomas | TIBKAT | 2021


    Genetic Algorithm Selection for Ship Concept Design

    Sobey, Adam / Grudniewski, Przemyslaw / Savasta, Thomas | Springer Verlag | 2020


    Team-Based Collaboration in Model-Based Design

    Mahapatra, Saurabh / Ghidella, Jason / Walker, Gavin | AIAA | 2012


    Team-Based Collaboration in Model-Based Design

    Ghidella, J. / Walker, G. / Mahapatra, S. et al. | British Library Conference Proceedings | 2012