• Title/Summary/Keyword: fast messy genetic algorithm(fmGA)

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Optimization Model for Sewer Rehabilitation Using Fast Messy Genetic Algorithm (fmGA를 이용한 하수관거정비 최적화 모델)

  • Ryu, Jae-Na;Ki, Beom-Joon;Rark, Kyoc-Hong;Lee, Cha-Don
    • Journal of Korean Society of Water and Wastewater
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    • v.18 no.2
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    • pp.145-154
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    • 2004
  • A long-term sewer rehabilitation project consuming an enormous budget needs to be conducted systematically using an optimization skill. The optimal budgeting and ordering of priority for sewer rehabilitation projects are very important with respect to the effectiveness of investment. In this study, the sewer rehabilitation optimization model using fast-messy genetic algorithm is developed to suggest a schedule for optimal sewer rehabilitation in a subcatchment area by modifying the existing GOOSER$^{(R)}$ model having been developed using simple genetic algorithm. The sewer rehabilitation optimization model using fast-messy genetic algorithm can improve the speed converging to the optimal solution relative to GOOSER$^{(R)}$, suggesting that it is more advantageous to the sewer rehabilitation in a larger-scale subcatchment area than GOOSER.