DOI QR코드

DOI QR Code

유입량의 변동성을 고려한 저수지 연계 운영 모형의 가중치 선정

Determination of Weight Coefficients of Multiple Objective Reservoir Operation Problem Considering Inflow Variation

  • 김민규 (고려대학교 정보경영공학전문대학원) ;
  • 김재희 (군산대학교 경영회계학부) ;
  • 김승권 (고려대학교 정보경영공학부)
  • Kim, Min-Gyu (Graduate School of Information Management and Security, Korea Univ.) ;
  • Kim, Jae-Hee (School of Business Administration & Accounting, Kunsan Nat'l Univ.) ;
  • Kim, Sheung-Kown (Division of Information Management Engineering, Korea Univ.)
  • 발행 : 2008.01.31

초록

본 연구의 목적은 금강수계의 가장 효율적인 가중치를 찾을 수 있는 절차를 제시하는 것이다. 일반적으로 다목적 최적화 모형의 결과는 목적함수에 부여된 가중치에 크게 좌우되는 경향이 있다. 특히 다목적 저수지 운영 문제의 경우는 어떤 유입량 시나리오가 적용되느냐에 따라 그에 적합한 가중치가 크게 달라질 수 있다. 따라서 유입량의 변동성을 감안해서 저수지 운영자에게 적합한 초기 가중치를 적용하는 것은 매우 큰 의미가 있다. 이에 본 연구는 유입량의 불확실성을 감안하여 적절한 가중치군을 도출할 수 있는 절차를 제안한다. 제안한 절차에서는 다중목적 최적화모형(GA-CoMOM)을 통해 파레토 집합에 대응되는 가중치군을 도출하고, DEA-윈도우분석(DEA-window analysis)과 교차효율성 분석(cross-efficiency analysis)을 사용하여 후보 가중치에 대한 순위를 산정하고, 이 결과를 분석해서 적합한 가중치를 선정한다. 이 절차를 금강 수계 저수지군 연계 운영 문제에 적용한 결과 유입량의 불확실성을 감안해서 가중치를 설정할 수 있었다.

The purpose of this study is to propose a procedure that will be able to find the most efficient sets of weight coefficients for the Geum-River basin in Korea. The result obtained from multi-objective optimization model is inherently sensitive to the weight coefficient on each objective. In multi-objective reservoir operation problems, the coefficient setting may be more complicated because of the natural variation of inflow. Therefore, for multi-objective reservoir operation problems, it may be important for modelers to provide reservoir operators with appropriate sets of weight coefficients considering the inflow variation. This study presents a procedure to find an appropriate set of weight coefficients under the situation that has inflow variation. The proposed procedure uses GA-CoMOM to provide a set of weight coefficient sets. A DEA-window analysis and a cross efficiency analysis are then performed in order to evaluate and rank the sets of weight coefficients for various inflow scenarios. This proposed procedure might be able to find the most efficient sets of weight coefficients for the Geum-River basin in Korea.

키워드

참고문헌

  1. 건설교통부 (2001). 수자원장기종합계획(Water Vision 2020)
  2. 김승권, 박영준 (1998). '댐군의 연계운영을 위한 수학적 모형.' 한국수자원학회논문집, 한국수자원학회, 제31권, 제6호, pp. 779-793
  3. 김승권 (2006). '수자원 공학에서의 최적화 기법의 활용(Ⅲ).' 한국수자원학회지(물과 미래), 한국수자원학회, 제39권, 제9호, pp. 83-94
  4. 김재희, 김승권, 고익환 (2007). '다중 목적 저수지 운영 문제를 위한 CBITP와 NSGA-II의 비교.' 2007 대한토목학회 정기학술대회 발표논문집, 대한토목학회, pp. 1433- 1436
  5. 박경삼, 김윤태, 정홍식 (2005). 'DEA 및 DEA윈도우분석을 이용한 대규모 종합병원의 시대별 경영효율성 변화분석.' 경영학연구, 한국경영학회, 제34권, 제1호, pp. 267-287
  6. 전승목, 김재희, 김승권 (2008). 'DEA 순위결정절차를 이용한 파레토 최적해 평가 -저수지 최적 방류 계획 선정을 중심으로-.' IE Interfaces, 대한산업공학회 (인쇄중)
  7. 한국수자원공사 (2004). 다목적댐 운영 실무편람
  8. Adler, N., Friedman, L., and Sinuany-Stern, Z. (2002). 'Review of ranking methods in the data envelopment analysis context.' European Journal of Operational Research, Elsevier, Vol. 140, pp. 249-265 https://doi.org/10.1016/S0377-2217(02)00068-1
  9. Banker, R.D., Charnes, A., and Cooper, W.W. (1984). 'Some models for estimating technical and scale inefficiencies in data envelopment analysis' Management Science, INFORMS, Vol. 30, No. 9, pp. 1078-1092 https://doi.org/10.1287/mnsc.30.9.1078
  10. Charnes, A., Cooper, W.W., and Rhodes, E. (1978). 'Measuring the efficiency of decision making units.' European Journal of Operational Research, Elsevier, Vol. 2, pp. 429-444 https://doi.org/10.1016/0377-2217(78)90138-8
  11. Charnes, A., Clark, C.T., Cooper, W.W., and Golany, B. (1985). 'A development study of data envelopment analysis in measuring the efficiency of maintenance units in the U.S. air forces.' Annals of Operations Research, Baltzer Science Publishers, Vol. 2, No. 1, pp. 95-112 https://doi.org/10.1007/BF01874734
  12. Doyle, J., and Green, R. (1994). 'Efficiency and cross-efficiency in data envelopment analysis: derivatives, meanings and uses.' Journal of the Operational Research Society, Operational Research Society, Vol. 45, No. 5, pp. 567-578 https://doi.org/10.2307/2584392
  13. Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. John Wiley & Sons, Chichester
  14. Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002). 'A fast and elitist multiobjective genetic algorithm: NSGA-II.' IEEE Transactions on Evolutionary Computation, IEEE, Vol. 6, No. 2, pp. 182-197 https://doi.org/10.1109/4235.996017
  15. Hwang, C.L., and Lin, M.J. (1987). Group decision making under multiple criteria. Springer Verlag, Berlin
  16. Kim, J.H., and Kim, S.K. (2006). 'A CHIM based interactive tchebycheff procedure for multiple objective decision making.' Computers and Operations Research, Elsevier, Vol. 33, No. 6, pp. 1577-1574 https://doi.org/10.1016/j.cor.2004.11.007
  17. Kim, S.K., Lee, Y.D., Kim, J.H., and Ko, I.H. (2005). 'A multiple objective mathematical model for daily coordinated multi-reservoir operation.' Water Science and Technology : water supply, Inter- national Water Association, Vol. 5, No. 3-4, pp. 81-88
  18. Labadie, J.W. (2004). 'Optimal operation of multireservoir systems: state-of-art review.' Journal of Water Resources Planning and Management, ASCE, Vol. 130, No. 2, pp. 93-111 https://doi.org/10.1061/(ASCE)0733-9496(2004)130:2(93)
  19. Lee, Y.D., Kim, S.K., and Ko, I.H. (2007). 'Genetic algorithm to determine weighting factors in multiple objective reservoir operation model under inflow uncertainty.' Working Paper, Korea University
  20. Simonovic, S., and Marino, M. (1982). 'Reliability programming in reservoir management 3: systems of multi-purpose reservoirs.' Water Resources Research, AGU, Vol. 18, No. 4, pp. 735-743 https://doi.org/10.1029/WR018i004p00735
  21. Steuer, R.E. (1986). Multiple Criteria Optimization: Theory, Computation, and Application. John Wiley & Sons, New York
  22. Yeh, W.W.-G. (1985). 'Reservoir management and operations models : A state of art review.' Water Resources Research, AGU, Vol. 21, No. 12, pp. 1797-1818 https://doi.org/10.1029/WR021i012p01797

피인용 문헌

  1. Development and Assessment of Hedging Rule for Han River Reservoir System Operation against Severe Drought vol.47, pp.10, 2014, https://doi.org/10.3741/JKWRA.2014.47.10.891
  2. Assessment of climate change impacts on the hydrology of Gilgel Abay catchment in Lake Tana Basin, Ethiopia 2009, https://doi.org/10.1002/hyp.7363
  3. An Evaluation of Multi-Reservoir Operation Weighting Coefficients Using Fuzzy DEA taking into account Inflow Variability vol.24, pp.3, 2011, https://doi.org/10.7232/IEIF.2011.24.3.220
  4. Improving Reservoir Operation Criteria to Stabilize Water Supplies in a Multipurpose Dam: Focused on Nakdong River Basin in Korea vol.10, pp.9, 2018, https://doi.org/10.3390/w10091236