Research On 3D Rectangular Layout Model And Layout Genetic Algorithm

Packing problem has a wide application, for example, in mechanical engineering,aerospace,robot path planning, leather garments industry, plate processing, shipbuilding and transportation,and many other industrial production in practice. A good layout design scheme can bring thehuge economic benefits for a enterprise, so the research on layout is of great practicalsignificance. In the theory layer, packing problem has been proved to be NP-hard problem. It isvery difficult to get the global optimal solution in a certain time. So the research about thepacking problem also has important theoretical significance.Firstly, this paper puts forward an algorithm to solve the geometrical feasible region ofpacking items in any packing space according to the characteristics of the spatial packing. It isthe algorithm of solving geometrical feasible region of packing items based on space partition.This algorithm is mainly composed of narrowing packing space, expanding packing items, andreducing operation. The geometrical feasible region of packing items is gotten in the end.Secondly, this paper proposes a kind of layout algorithm which is based on three sequencesand geometrical feasible region of packing items. Then the packing algorithm is optimized bygenetic algorithm. The main idea of packing is that in the solving process the relative position ofthe packing items in packing space which are presented in the three sequences is expressed in thehelp of graph theory. Then the packing position is determined. Compare this position with otherpositions in the geometrical feasible region, find the best packing position for the packing items.Thirdly, this paper use Bee Evolutionary Genetic Algorithm to optimize the parameters inattractor placement function to solve the three-dimension packing problem. This algorithmmakes full use of the optimum individual in the population to the population evolution. At thesame time, in order to maintain the diversity of population, the "exotic species" thought in thebee breeding process is introduced. The target of the algorithm is the largest volume utilizationof the packing space. The order to pack the packing items is decided by the volume of thepacking items. The location problem is solved by attractor placement function and geometricalfeasible region of packing items. Then the packing of items is accomplished.At last, the work of this paper is summarized, and the work need to do in the future issuggested.