Improvement on genetic algorithms and its application in fluid machinery
Tao Haikun1, Tan Lei2, Cao Shuliang2
（1.Wuhan Second Ship Design and Research Institute, Wuhan, Hubei 430064, China; 2.State Key Laboratory of Hydroscience and Engineering, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China)
GA(genetic algorithms) was overall improved: roulette wheel selection based on sorting, excellent selection strategy was used in selection operator, heuristic crossover was used in crossover operator,adaptive nonunformity variation was used in variation operation, also, cross century elite choosing strategy and niche strategy were introduced. Traditional GA is easy to generate premature phenomena and get the local optimal solution. Improved-GA which overcomes the disadvantages of traditional GA speeds up the convergence rate. The population size selected by improved-GA is small, so as to reduce the calculation work. The relationship of design parameters and outlet velocity uniformity of bell-like inlet passage was researched using improved-GA and CFD. The results indicate that the improved-GA can successfully apply to multi-parameter optimization design of bell like inlet passage. The hydraulic performance of bell-like inlet passage is greatly improved. Objective function values of two parameters and five parameters are 96.817% and 97.285%, respectively. This study provides references for engineering applications.
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