산업공학 (IE interfaces)

  • 제22권3호
  • /
  • Pages.223-233
  • /
  • 2009
  • /
  • 1225-0996(pISSN)
  • /
  • 2234-6465(eISSN)
대한산업공학회 (Korean Institute of Industrial Engineers)
권호 표지

유전자 알고리즘을 이용한 동사무소 통폐합 최적화방안 연구

A Study on the Optimal Planning for Dong Office Location by Genetic Algorithm

  • 박인옥 (서울산업대학교산업정보시스템공학과) ;
  • 김우제 (서울산업대학교산업정보시스템공학과)
  • Park, In-Ok (Dept. of Industrial and Information Systems Engineering, Seoul National University of Technology) ;
  • Kim, Woo-Je (Dept. of Industrial and Information Systems Engineering, Seoul National University of Technology)
  • 투고 : 2009.05.15
  • 심사 : 2009.08.04
  • 발행 : 2009.09.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this paper we developed a method for an optimal planning to reorganize Dong offices to enhance the administrative efficiency. First we defined a mathematical model for the optimal planning problem of reorganizing Dong office and developed a genetic algorithm to solve the problem. For the purpose of minimizing standard deviation of population, area and distance among reorganized offices, the constraints such as allocation, distance, area, population, etc. are considered and weights are applied to Dong offices in the downtown and shopping area. The developed algorithm was applied for reorganizing Dong offices in Jongro Gu, Seoul. The results showed that the developed algorithm could be applied for the real world problem. This study may be applied to the optimal decision of reorganization of offices in the similar reorganization or company M&A situations by changing constraints and weights.

키워드

참고문헌

  1. Administration Division, Seoul City (2007), Master plan for reorganizing Dong Office
  2. Ministry of Government Administration and Home Affairs (2007), The Guidelines for reorganization of small Dong Office
  3. Jongro-gu Office (2007). Execution plan for integrating Dong-office and adjusting administrative districts
  4. http://www.seoul.go.kr/seoul/summary/statistics/briefing/index_v2007.html.
  5. http://gis.seoul.go.kr/StatisticalMap/index.jsp
  6. Cha, B-C. andKim,W-S. (2007), Simulator for restrict adjustment ofmail sorting centers : A case study, IE Interfaces, 20(4), 515-524
  7. Mun, S-M. (2003),Multiple objective location -allocation problemsolving using Genetic Algorithms,Yonsei UniversityMaster’s degree thesis
  8. Min, B-G. (2006), Astudy on facility location problemdue to themigration using Genetic Algorithm,National DefenseUniversityMaster’s degree thesis
  9. Jeong, Y-J. (2004), Hybrid application of fuzzy goal programming and GeneticAlgorithmfor plant location problem,Yonsei UniversityMaster’s degree thesis
  10. Park, Y-C., Lee, C-W., and Hwang, H-S. (1996), The analysis and optimal selection on the location of public service :Gu-office, fire station, and Post office in Ulsan, Korea, Journal of Korea Regional Development, 8(1), 23-53
  11. Lee, C-W., Kwon, S-B., Gang, J-S., Gang, C-G., and Kim, J-N. (1998), The Study of mailing center location using the AHP methodology,Policy Analysis Assessment, 9(2)
  12. Perl, Jossef and Ho, Peng-Kuan (1990), Public Facilities Location under Elastic Demand,Transportation Science, 24, 117-136 https://doi.org/10.1287/trsc.24.2.117
  13. Beasley, J. E. and Chu, P. C. (1996), A Genetic Algoritem for the Set Covering Problem, European Journal of Operational Research, 94, 392-404 https://doi.org/10.1016/0377-2217(95)00159-X
  14. Hodgart, R. L. (1978), Optimizing Access to Public Service : A Review of Problems, Models and Methods of Locating Central Facilities, Progress in HumanGeography, 2(1), 17-48 https://doi.org/10.1177/030913257800200103