Minimizing the loss of raw materials is an important issue in the construction industry. The construction material often encounters two-dimensional cutting problems such as steel plates and wooden plates. Reducing material waste by using building information modeling (BIM) and artificial intelligence methods has received considerable attention. Thus, this study focused on two-dimensional cutting stock problems (2D-CSP), and employed the auto-tuning Symbiotic Organisms Search algorithm (SOS) to establish residual material optimization model. The results considering the placement strategy with the rotation of the cutting plates, showed that, compared to other heuristic algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), the SOS algorithm obtained superior solutions to the two-dimensional cutting operation. Therefore, the proposed model possesses a certain application value for solving the optimization problem in the construction industry, and helps reducing the material waste and budget cost.


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    Titel :

    Auto-tuning SOS Algorithm for Two-Dimensional Orthogonal Cutting Optimization


    Weitere Titelangaben:

    KSCE J Civ Eng


    Beteiligte:
    Cheng, Min-Yuan (Autor:in) / Fang, Yi-Cho (Autor:in) / Wang, Chun-Yao (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2021-10-01


    Format / Umfang :

    15 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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