Engineering Optimization · 2006 · 527 citations · 27 references
EngineeringCivil EngineeringWater Resources ManagementDesign OptimizationOptimizationWater Resources EngineeringCombinatorial OptimizationDistribution Network DesignGenetic AlgorithmsHeuristic OptimizationMetaheuristic OptimizationWater Distribution SystemsHarmony SearchHeuristic AlgorithmsOptimal DesignTabu SearchWater Distribution DesignWater Distribution System DesignWater Distribution System OptimizationWater Network Design
The harmony search algorithm, inspired by jazz improvisation, is used to optimize pipe diameters in water distribution networks. This study introduces a cost‑minimization model for designing water distribution networks. The model applies a harmony search optimizer linked to EPANET, penalizing hydraulic constraint violations within the cost function. Testing on five networks yielded designs that were equivalent or 0.28–10.26 % cheaper than those from genetic algorithm, simulated annealing, and tabu search, confirming the model’s effectiveness.
This study presents a cost minimization model for the design of water distribution networks. The model uses a recently developed harmony search optimization algorithm while satisfying all the design constraints. The harmony search algorithm mimics a jazz improvisation process in order to find better design solutions, in this case pipe diameters in a water distribution network. The model also interfaces with a popular hydraulic simulator, EPANET, to check the hydraulic constraints. If the design solution vector violates the hydraulic constraints, the amount of violation is considered in the cost function as a penalty. The model was applied to five water distribution networks, and obtained designs that were either the same or cost 0.28–10.26% less than those of competitive meta-heuristic algorithms, such as the genetic algorithm, simulated annealing and tabu search under similar or less favorable conditions. The results show that the harmony search-based model is suitable for water network design.
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Genetic algorithms in search, optimization, and machine learning
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Scott Kirkpatrick, C. D. Gelatt, M.P. Vecchi · Science · 1983 · 44.6K citations
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Kenneth DeJong · Deep Blue (University of Michigan) · 1975 · 1.3K citations · Full text
Life Sciences, Biology, Genetics +12