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http://dx.doi.org/10.5762/KAIS.2020.21.5.294

Efficiency Evaluation of Genetic Algorithm Considering Building Block Hypothesis for Water Pipe Optimal Design Problems  

Lim, Seung Hyun (Department of Civil Engineering, The University of Suwon/Institute River Environmental Technology)
Lee, Chan Wook (Department of Civil Engineering, The University of Suwon/Institute River Environmental Technology)
Hong, Sung Jin (Department of Civil Engineering, The University of Suwon/Institute River Environmental Technology)
Yoo, Do Guen (Department of Civil Engineering, The University of Suwon/Institute River Environmental Technology)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.21, no.5, 2020 , pp. 294-302 More about this Journal
Abstract
In a genetic algorithm, computer simulations are performed based on the natural evolution process of life, such as selection, crossover, and mutation. The genetic algorithm searches the approximate optimal solution by the parallel arrangement of Schema, which has a short definition length, low order, and high adaptability. This study examined the possibility of improving the efficiency of the optimal solution by considering the characteristics of the building block hypothesis, which are one of the key operating principles of a genetic algorithm. This study evaluated the efficiency of the optimization results according to the gene sequence for the implementation in solving problems. The optimal design problem of the water pipe was selected, and the genetic arrangement order reflected the engineering specificity by dividing into the existing, the network topology-based, and the flowrate-based arrangement. The optimization results with a flowrate-based arrangement were, on average, approximately 2-3% better than the other batches. This means that to increase the efficiency of the actual engineering optimization problem, a methodology that utilizes clear prior knowledge (such as hydraulic properties) to prevent such excellent solution characteristics from disappearing is essential. The proposed method will be considered as a tool to improve the efficiency of large-scale water supply network optimization in the future.
Keywords
Genetic Algorithm; Building Block Hypothesis; Pipe Size Design; Optimization; Water Distribution Systems;
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