B2B, B2C 물류 환경을 고려한 3차원 차량 적재 알고리즘 개발

초록

As a part of the transition to the logistics 4.0 era, automation and unmanned technology have become the biggest issues in the logistics industry based on the development of various technologies such as AI and robotics. Due to the high workload of logistics activities, automation of loading operation is regarded as the one of the most important topics in logistics field. The automation of the loading operation is expected to provide a higher work efficiency as well as a relaxation of the labor intensity during the loading process. In addition, optimization of the loading space will leads to the reduction of environmental pollution and carbon emission by minimizing idle spaces. This study aims to support the automation of the loading process in various logistics environments by developing efficient 3-Dimensional (3D) loading algorithms applicable to the actual logistics environment of B2B and B2C cases. Realistic considerations such as unloading order preferences, height limitation, and product rotation are addressed to achieve such applicablities. The performance of the proposed algorithms was tested via realistic numerical examples.

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