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The Big Bang-Big Crunch (BB–BC) method is a relatively new meta-heuristic algorithm which inspired by one of the theories of the evolution of universe. In the BB–BC optimization algorithm, firstly random points are produced in the Big Bang phase then these points are shrunk to a single representative point via a center of mass or minimal cost approach in the Big Crunch phase. In this paper, the BB–BC algorithm is presented for optimal cost design of water distribution systems and employed to optimize different types of hydraulic networks with discrete variables. The results demonstrate the efficiency of the proposed method compared to other algorithms.

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The present study encompasses a new method to simultaneous analysis, design and optimization of Water Distribution Systems (WDSs). In this method, analysis procedure is carried out using Charged System Search (CSS) optimization algorithm. Besides design and cost optimization of WDSs are performed simultaneous with analysis process using a new objective function in order to satisfying the analysis criteria, design constraints and cost optimization. Comparison of achieved results clearly signifies the efficiency of the present method in reducing the WDSs construction cost and computational time of the analysis. These comparisons are made for three benchmark practical examples of WDSs.

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This paper describes the application of the recently developed metaheuristic algorithm for simultaneous analysis, design and optimization of Water Distribution Systems (WDSs). In this method, analysis is carried out using Colliding Bodies Optimization algorithm (CBO). The CBO is a population-based search approach that imitates nature’s ongoing search for better solutions. Also, design and cost optimization of WDSs are performed simultaneous with analysis process using a new objective function in order to satisfying the analysis criteria, design constraints and cost optimization. A number of practical examples of WDSs are selected to demonstrate the efficiency of the presented algorithm. Comparison of obtained results clearly signifies the efficiency of the CBO method in reducing the WDSs construction cost and computational time of the analysis.

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In this study, the recently developed method, Tug of War Optimization (TWO), is employed for simultaneous analysis, design and optimization of Water Distribution Systems (WDSs). In this method, analysis procedure is carried out using Tug of War Optimization algorithm. Design and cost optimization of WDSs are performed simultaneous with analysis process using an objective function in order to satisfying the analysis criteria, design constraints and cost optimization. A number of practical examples of WDSs are selected to demonstrate the efficiency of the presented algorithm. The findings of this study clearly signify the efficiency of the TWO algorithm in reducing the water distribution networks construction cost.

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Leakage detection in water distribution systems play an important role in storage and management of water resources. Therefore, to reduce water loss in these systems, a method should be introduced that reacts rapidly to such events and determines their occurrence time and location with the least possible error. In this study, in order to determine position and amount of leakage in distribution system, a detection method based on hydraulic model was evaluated using Extended Kalman Filter (EKF), which is a non-linear Kalman Filter. The results indicated that the method was well able to predict leakage position and its amount. Using a numerical model, a leakage was placed in 25.4 m distance of its upstream, amounting to 1.33 lit/sec which was equal to 10 percent of overall flow. The calculated mean position and leakage value by EKF were 27.17 m and 1.11 lit/sec, respectively.

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Water distribution networks are one of the important and costly infrastructures of cities and many meta-heuristic algorithms in standard or hybrid forms were used for optimizing water distribution networks. These algorithms require a large amount of computational cost. Therefore, the converging speed of algorithms toward the optimization goal is as important as the goal itself. In this paper, a new method is developed by linking the charged system search algorithm and firefly algorithm for optimizing water distribution networks. For evaluating the proposed method, some popular benchmark examples are considered. Simulation results demonstrate the efficiency of the proposed algorithm compared to others.