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An Optimization Method of Spatial Placement for Effective Vehicle Loading

효과적인 차량 선적을 위한 공간 배치의 최적화 기법

  • Cha, Joo Hyoung (Division of Creative Software Eng., Dong-eui University) ;
  • Choi, Jin Seok (Logistics System Institute, Total Soft Bank Ltd.) ;
  • Bae, You Su (Logistics System Institute, Total Soft Bank Ltd.) ;
  • Woo, Young Woon (Division of Creative Software Eng., Dong-eui University)
  • Received : 2019.12.21
  • Accepted : 2020.01.03
  • Published : 2020.02.29

Abstract

In this paper, we proposed an optimization technique for efficiently placing vehicles on decks in a vehicle-carrying ship to efficiently handle loading and unloading. For this purpose, we utilized the transformation method of the XML data representing the ship's spatial information, merging and branching algorithm and genetic algorithm, and implemented the function to visualize the optimized vehicle placement results. The techniques of selection, crossover, mutation, and elite preservation, which are used in the conventional genetic algorithms, are used. In particular, the vehicle placement optimization method is proposed by merging and branching the ship space for the vehicle loading. The experimental results show that the proposed merging and branching method is effective for the optimization process that is difficult to optimize with the existing genetic algorithm alone. In addition, visualization results show vehicle layout results in the form of drawings so that experts can easily determine the efficiency of the layout results.

이 논문에서는 차량 운반선에서 선적 계획과 하적 계획에 따른 차량 선적을 효과적으로 진행하기 위하여, 선박 내 데크에 차량을 효율적으로 배치하는 최적화 기법을 제안하였다. 이를 위해, 선박의 공간 정보를 나타내는 XML 데이터의 변환, 병합 및 분할 알고리즘, 유전자 알고리즘을 활용하였으며, 또한 최적화된 차량 배치 결과를 시각화하는 기능까지 구현하였다. 기존의 전형적인 유전자 알고리즘에서 사용되는 선택, 교차, 변이, 엘리트 보존 등의 기법들을 활용하였으며, 특히 차량의 선적을 위한 선박 공간을 병합 및 분할하는 기법을 함께 제안하여 차량 배치 최적화 기법을 제안하였다. 실험 결과, 기존의 유전자 알고리즘만으로 최적화하기 힘든 부분에 제안한 병합 및 분할 기법을 적용하는 것이 최적화 과정에 효과적이었음을 확인할 수 있었다. 또한, 시각화 기법을 통해 차량 배치 결과를 도면 형태로 보여줌으로써 배치 결과의 효율성을 전문가가 쉽게 판단할 수 있도록 하였다.

Keywords

References

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