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Optimization Model for Sewer Rehabilitation Using Fast Messy Genetic Algorithm  

Ryu, Jae-Na (중앙대학교 토목공학과)
Ki, Beom-Joon (중앙대학교 토목공학과)
Rark, Kyoc-Hong (중앙대학교 토목공학과)
Lee, Cha-Don (중앙대학교 건축공학과)
Publication Information
Journal of Korean Society of Water and Wastewater / v.18, no.2, 2004 , pp. 145-154 More about this Journal
Abstract
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.
Keywords
optimization; sewer rehabilitation; optimal budgeting; fast messy genetic algorithm(fmGA);
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