Abstract
Water supply systems are mainly classified into branched and looped network systems. The main difference between these two systems is that, in a branched network system, the flow within each pipe is a known value, whereas in a looped network system, the flow in each pipe is considered an unknown value. Therefore, an analysis of a looped network system is a more complex task. This study aims to develop a technique for estimating the optimal pipe diameter for a looped agricultural irrigation water supply system using a harmony search algorithm, which is an optimization technique. This study mainly serves two purposes. The first is to develop an algorithm and a program for estimating a cost-effective pipe diameter for agricultural irrigation water supply systems using optimization techniques. The second is to validate the developed program by applying the proposed optimized cost-effective pipe diameter to an actual study region (Saemangeum project area, zone 6). The results suggest that the optimal design program, which applies an optimization theory and enhances user convenience, can be effectively applied for the real systems of a looped agricultural irrigation water supply.
Highlights
Water supply systems are mainly classified into branched and looped network systems
The developed program was applied to the actual target area
Used methods have disadvantages in that the pipe diameter has to be adjusted through a hydraulic calculation of the given water supply network, and this process has to be repeated until satisfactory results are obtained
Summary
Water supply systems are mainly classified into branched and looped network systems. The main difference between the two is that, in a branched network system, the flow within each pipe is a known value, whereas in a looped network system, the flow within each pipe is considered an unknown value. If the initial solution is not located at a good position within the solution zone, the global optimum is unobtainable, and the initial solution cannot escape from the local optima To overcome these disadvantages, during the last 20 years, researchers have attempted to apply new approaches to optimization technologies that do not use an existing mathematical methodology. Hybrid versions of existing algorithms and new algorithms have been developed such as Genetic Heritage Evolution by Stochastic Transmission (GHEST, [13]), NLPDifferential Evolution algorithm (Combined NLP-DE, [14]), Hybrid Particle Swarm Optimization and Differential Evolution (Hybrid PSO-DE, [15]), and Charged System Search algorithm (CSS, [16]) Most of these studies have disadvantages in that they were applied to small benchmark problems and were not reflected in the actual plans [17]. Division and facilities Agricultural lands U-complex urban lands Industrial lands (free economic zone (FEZ)) Science and research lands New and renewable energy lands Urban lands Sinsi-Yami multifunctional lands Ecological and environmental lands Water proof facilities and so forth Total
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