Abstract
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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Abbreviations
- b j :
-
Total amount of type j cut plates
- largest_ERS :
-
Largest area of the residual material
- L i :
-
The original length of the i-th plate
- l j :
-
Type j cut plate length
- K :
-
Is a constant and is recommended to be set between 0.01 and 0.1 [19]
- n :
-
Type of cut plates
- p :
-
Type of cut plates
- s:
-
Number of material plates
- small_piecei :
-
Smallest area in the cut plates
- W i :
-
The original length of the i-th plate
- w j :
-
Type j cut plate width
- x j :
-
Number of type j cut plates
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Cheng, MY., Fang, YC. & Wang, CY. Auto-tuning SOS Algorithm for Two-Dimensional Orthogonal Cutting Optimization. KSCE J Civ Eng 25, 3605–3619 (2021). https://doi.org/10.1007/s12205-021-0522-y
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DOI: https://doi.org/10.1007/s12205-021-0522-y