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Optimal Design of Water Distribution Network Using Improved Artificial Bee Colony Algorithm
Urban water distribution networks are the most essential and costly network in each city. Major part of the urban water distribution network costs are related to the purchase of water distribution network accessories. Therefore, the cost of the water distribution network can be reduced by reducing this part. For this purpose, the design of water distribution network should be defined as an optimization model and solved it using an efficient method. Nowadays, meta-heuristics algorithms are the most efficient methods for solving optimization models. In this research, three benchmark problems, mean two-loop, New York, and Go Yang networks, are modeled in EPANET software and the optimization model is solved using an improved version of the artificial bee colony algorithm that is called in MATLAB software. To evaluate the efficiency of the proposed algorithm, the results are presented and compared with the standard version of the artificial bee colony algorithm and other available results. The results show that by using an improved artificial bee colony algorithm for two-loop network, New York, and Go Yang network, the objective function values (construction costs) and computational costs are 419,000 unit, 38.13 M$, and 175.78 MWon and 2500, 3600, and 2600, respectively. In addition, comparison of the results shows that the construction and computational costs are reduced compared with the result of the standard version.
Optimal Design of Water Distribution Network Using Improved Artificial Bee Colony Algorithm
Urban water distribution networks are the most essential and costly network in each city. Major part of the urban water distribution network costs are related to the purchase of water distribution network accessories. Therefore, the cost of the water distribution network can be reduced by reducing this part. For this purpose, the design of water distribution network should be defined as an optimization model and solved it using an efficient method. Nowadays, meta-heuristics algorithms are the most efficient methods for solving optimization models. In this research, three benchmark problems, mean two-loop, New York, and Go Yang networks, are modeled in EPANET software and the optimization model is solved using an improved version of the artificial bee colony algorithm that is called in MATLAB software. To evaluate the efficiency of the proposed algorithm, the results are presented and compared with the standard version of the artificial bee colony algorithm and other available results. The results show that by using an improved artificial bee colony algorithm for two-loop network, New York, and Go Yang network, the objective function values (construction costs) and computational costs are 419,000 unit, 38.13 M$, and 175.78 MWon and 2500, 3600, and 2600, respectively. In addition, comparison of the results shows that the construction and computational costs are reduced compared with the result of the standard version.
Optimal Design of Water Distribution Network Using Improved Artificial Bee Colony Algorithm
Iran J Sci Technol Trans Civ Eng
Najarzadegan, Mohammad Reza (author) / Moeini, Ramtin (author)
2023-10-01
14 pages
Article (Journal)
Electronic Resource
English
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