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- W3169307923 abstract "Shell-and-tube heat exchangers are important equipment used in every transformation industry. The mathematical models that describe the thermo-hydraulic behavior of these equipment generates a complex search space. Due this complexity, traditional gradient-based algorithms fail to converge in the neighborhood of the global optima. Metaheuristic methods are global search strategies that implements different operators to avoid local optima solution. In this work four case studies for the optimization of shell-and-tube heat exchangers are considered. For each case study the use of Kern's and Bell-Delaware methods is contemplated with discrete and continuous diameters of tubes, resulting in a total of 16 optimization problems (four optimization problems per case study), where the objective function is the total annual cost of the equipment. Seven metaheuristic algorithms are employed to solve each optimization problem; their performance is compared using statistical parameters such as the mean, median and standard deviation of the objective function. The metaheuristic algorithms with the best global performance are differential evolution and grey wolf optimization." @default.
- W3169307923 created "2021-06-22" @default.
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- W3169307923 date "2021-09-01" @default.
- W3169307923 modified "2023-10-18" @default.
- W3169307923 title "Comparison of the performance of different metaheuristic methods for the optimization of shell-and-tube heat exchangers" @default.
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- W3169307923 doi "https://doi.org/10.1016/j.compchemeng.2021.107403" @default.
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