An enhanced genetic algorithm-based multi-objective design optimization strategy

被引：19
|
作者：
Yuan, Rong [1 ,2 ]
Li, Haiqing [3 ]
Wang, Qingyuan [1 ,2 ]
机构：
[1] Chengdu Univ, Sch Mech Engn, Chengdu, Sichuan, Peoples R China
[2] Sichuan Univ, Coll Architecture & Environm, Chengdu, Sichuan, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Mech & Elect Engn, Chengdu, Sichuan, Peoples R China
来源：
ADVANCES IN MECHANICAL ENGINEERING | 2018年 / 10卷 / 07期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Enhanced genetic algorithm; ratio of conformity; multi-objective design and optimization; preference chosen; speed increaser; MULTIDISCIPLINARY DESIGN; SYSTEM; PROBABILITY;
D O I：
10.1177/1687814018784836
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
In this study, an enhanced genetic algorithm is proposed to solve multi-objective design and optimization problems in practical engineering. In the given approach, designers choose available design results from the given samples first. These samples are re-ordered according to their mutual relationships. After that, designers choose an exact ratio of conformity as available field. Furthermore, more weight information can be obtained through finding the minimum value of the norm of unconformity and satisfactory samples. These samples can be used to reflect the preference chosen for Pareto design solutions. A structure design problem of speed increaser used in wind turbine generator systems is solved to show the application of the given design strategy.
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页数：6
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