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《Journal of Railway Science and Engineering》 2011-02
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Optimization model for locomotive secondary spring load adjustment based on multi-objective genetic algorithm

PAN Di-fu,ZHU Ya-nan(School of Traffic & Transportation Engineering,Central South University,Changsha 410075,China)  
In order to improve the practicability of optimization algorithm for locomotive secondary spring load adjustment,and to solve the problem of excessive gasket quantity generated by single-objective genetic algorithm,a method based on multi-objective genetic algorithm was presented.The multi-objective optimization model was built according to the preference structure of the problem,and the spring adjustment objective function was designed based on multi-objective genetic algorithm,the adaptive weight approach was introduced further to obtain the objective function value,the relevant method of fitness evaluation and distribution was also established.Results of the application to SS3b and HXD1B locomotives show that the new approach has the capability to reduce the gasket quantity by 48% as well as optimize the secondary load distribution,the availability and reliability of the spring adjustment algorithm is enhanced significantly.
【CateGory Index】: U260.72
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