Development of Global Optimization Method for Design of Turbine Stages
Hiroyuki Kawagishi, Kazuhiko KUDO
Abstract
Hiroyuki Kawagishi, Kazuhiko KUDO
Abstract
A new optimization method which can search for the global optimum solution and decrease the number of iterations was developed. The performance of the new method was found to be effective in finding the optimum solution for single- and multi-peaked functions for which the global optimum solution was known in advance. According to the application of the method to the optimum design of turbine stages, it was shown that the method can search the global optimum solution at approximately one seventh of the iterations of GA (Genetic Algorithm) or SA (Simulated Annealing).
OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
A new optimization method which can search for the global optimum solution and decrease the number of iterations was developed. The performance of the new method was found to be effective in finding the optimum solution for single- and multi-peaked functions for which the global optimum solution was known in advance. According to the application of the method to the optimum design of turbine stages, it was shown that the method can search the global optimum solution at approximately one seventh of the iterations of GA (Genetic Algorithm) or SA (Simulated Annealing).
Key concepts: Simulated annealing, Global optimization, Mathematical optimization, Turbine, Genetic algorithm, Computer science, Mathematics, Engineering