Abstract

Packing problems on its current state are being utilized for wide area of industrial applications. The aim of present research is to create and implement an intelligent system that tackles the problem of 2D packing of objects inside a 2D container, such that objects do not overlap and the container area is to be maximized. The packing problem becomes easier, when regular/rectangular objects and container are used. In most of the practical situations, the usage of irregular objects comes to existence. To solve the packing problem of irregular objects inside a rectangular container, a hybrid intelligence approach is introduced in our proposed work. The combination of machine intelligence and human intelligence is referred as the hybrid intelligence or semi-automated approach in the proposed methodology. The incorporation of human intelligence in the outcome of machine intelligence is possible to obtain using the internet crowdsourcing as we wish to handle the packing problem through internet crowdsourcing involving rural people. The proposed methodology is tested on different standard data sets and it is observed that it has clear advantage over both manual as well as fully automated heuristic based methods in terms of time and space efficiency.

Highlights

  • Human intelligence used in geometric reasoning about shapes, regardless of their educational and social background, is more effective when compared to machine intelligence

  • In the 2D packing problems, it is observed that the manual approach as well as the fully automated heuristic-based approaches have their limitations as the manual approach usually takes more time for packing and the fully automated approach achieves limited space efficiency

  • The experiments on different types of criteria used in greedy algorithm of the proposed method on Albano data are depicted in the Figure.2 (c), (d), (e), and (f)

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Summary

Introduction

Human intelligence used in geometric reasoning about shapes, regardless of their educational and social background, is more effective when compared to machine intelligence. In the 2D (two dimensional) packing problems, it is observed that the manual approach as well as the fully automated heuristic-based approaches have their limitations as the manual approach usually takes more time for packing and the fully automated approach achieves limited space efficiency. Further it is found that the amount of research work using both machine and human intelligence together is very much limited which is observed from the state of art review. By combining the human and machine intelligence which is referred as hybrid intelligence in our case, may provide better solution for the 2D packing problem. The hybrid intelligence approach is possible to obtain using the internet crowdsourcing where the outcome of machine intelligence approach for 2D packing may be further refined by a human

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