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DOI: 10.17587/it.28.339-347 V. A. Chekanin, Dr. Sc., Associate Professor, Moscow State University of Technology "STANKIN", Moscow, 127055, Russian Federation, Leading Researcher, V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, 117997, Russian Federation, Application of the Model of Potential Containers for Packing Complex Shape Objects The optimization problem of packing objects of arbitrary shape with generalization in dimension is considered. The purpose of this work is to develop and study algorithms that provide fast optimized placement of a large number of objects of arbitrary shape. To achieve this goal, the problem was set to improve the model of potential containers, originally developed for packing orthogonal objects in the form of rectangles or parallelepipeds. To quickly get layouts, it is proposed to switch from a polygonal representation of objects under placing to their discrete representation after voxelization. Obviously, when placing objects of complex shape are voxelized with a high degree of detail, a large number of potential containers will be formed, which will reduce the speed of solving the problem. This article presents the developed algorithms optimized by the number of potential containers processed to increase the speed of geometric design of a layout. Computational experiments have shown that the highest speed of the formation placement schemes of orthogonal polyhedrons is provided by using algorithms based on the application of the set-theoretic intersection operation. A method of removing unused potential containers is proposed, which allows several times to increase the speed of object placement. It is shown that the effectiveness of its application increases with an increase in the number of objects to be placed. A method for creating a container of complex shape form a polygonal model by applying an orthogonal polyhedron of geometric constraints to it is presented. All presented algorithms are implemented programmatically for the case of an arbitrary dimension of the problem being solved. P. 339–347 |