Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
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Selection of Appropriate Location for Civil Defense Shelters Using Genetic Algorithm and Network Analysis

유전자 알고리즘과 네트워크 분석을 활용한 민방위 대피시설 위치 선정

  • Yoo, Suhong (Dept. of Civil and Environmental Engineering, Yonsei University) ;
  • Kim, Mi-Kyeong (Dept. of Civil and Environmental Engineering, Yonsei University) ;
  • Bae, Junsu (Dept. of Civil and Environmental Engineering, Yonsei University) ;
  • Sohn, Hong-Gyoo (Dept. of Civil and Environmental Engineering, Yonsei University)
  • Received : 2018.11.22
  • Accepted : 2018.12.03
  • Published : 2018.12.31
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Abstract

Various studies have been conducted to analyze the location appropriateness and capacity of shelters. However, research on how to select new shelters is relatively insufficient. Since the shelter is designated in case of emergency, it is also necessary to efficiently select the location of the shelter. Therefore, this study presented a method for selecting the location of the shelter using network analysis that has been used to analyze the location appropriateness of shelters and genetic algorithm which is a representative heuristic algorithm. First, the network analysis using the existing civil defense evacuation facility data was performed and the result showed that the vulnerability of evacuation has a high deviation by region in the study area. In order to minimize the evacuation vulnerable area, the genetic algorithm was designed then the location of new shelters was determined. The initial solution consisting of candidate locations of new shelters was randomly generated and the optimal solution was found through the process of selection, crossover, and mutation. As a result of the experiment, the area with a high percentage of the evacuation vulnerable areas was prioritized and the effectiveness of the proposed method could be confirmed. The results of this study is expected to contribute to the positioning of new shelters and the establishment of an efficient evacuation plan in the future.

최근 대피시설의 위치 적절성, 수용 능력 등을 분석하기 위한 연구가 다양하게 진행되고 있으나, 신규 대피시설의 위치를 선정하는 방법에 관한 연구는 상대적으로 부족하다. 만일의 사태에 대비하기 위해서 대피시설을 지정하는 것이므로, 효율적으로 대피시설의 위치를 선정하는 방법 또한 필요하다. 따라서 본 연구에서는 대피시설의 입지 적절성 분석에 활용되어온 네트워크 분석과 대표적인 휴리스틱 알고리즘인 유전자 알고리즘을 활용하여 대피시설의 위치를 선정하는 방법을 제시하였다. 먼저, 기존의 민방위 대피시설 자료를 토대로 네트워크 분석을 시행하여 연구지역의 대피 취약지를 살펴본 결과, 지역별로 편차가 큰 것을 확인할 수 있었다. 이에 연구지역의 대피 취약지를 최소화하는 것을 목적함수로 유전자 알고리즘을 설계하여 신규 대피시설의 위치를 결정하였다. 대피시설 후보지의 위치로 구성된 초기해를 무작위로 생성하였고, 선택, 교차, 변이의 과정을 통해 목적함수를 최대로 만족하는 해를 탐색하였다. 실험결과, 연구지역 내 대피 취약지역의 비율이 높은 곳이 우선적으로 선정되었으며, 제안 기법의 효용성이 확인되었다. 본 연구의 결과는 향후 새로운 대피시설의 위치를 지정하고 효율적인 대피 계획을 수립하는 데에 기여할 수 있을 것으로 기대된다.

Keywords

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Fig. 1. Location of the study area (a) and its administrative boundary (b)

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Fig. 2. Flowchart of selecting the optimal location of new shelters

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Fig. 3. Schematic diagram of genetic algorithm in the study

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Fig. 4. Population density distribution (a) and the location of shelters (b) in the study area

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Fig. 5. Service area of shelters (walking speed: 4km/h)

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Fig. 6. Service area of shelters (walking speed:3.4km/h)

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Fig. 7. Location of newly selected shelters; (a) 5, (b) 10, (c) 15, (d) 20, (e) 25, (f) 30 (4km/h, 30min)

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Fig. 8. Location of newly selected shelters; (a) 5, (b) 10, (c) 15, (d) 20, (e) 25, (f) 30 (3.4km/h, 30min)

Table 1. Service area and the capacity of shelters by districts

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Table 2. Service area of shelters depending on the number of newly selected shelters

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