Improved Genetic Algorithm with Two-Level Approximation for Truss Optimization by Using Discrete Shape Variables
المؤلفون المشاركون
Huang, Hai
Chen, Shen-yan
Shui, Xiao-fang
Li, Dong-fang
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-09-16
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
This paper presents an Improved Genetic Algorithm with Two-Level Approximation (IGATA) to minimize truss weight by simultaneously optimizing size, shape, and topology variables.
On the basis of a previously presented truss sizing/topology optimization method based on two-level approximation and genetic algorithm (GA), a new method for adding shape variables is presented, in which the nodal positions are corresponding to a set of coordinate lists.
A uniform optimization model including size/shape/topology variables is established.
First, a first-level approximate problem is constructed to transform the original implicit problem to an explicit problem.
To solve this explicit problem which involves size/shape/topology variables, GA is used to optimize individuals which include discrete topology variables and shape variables.
When calculating the fitness value of each member in the current generation, a second-level approximation method is used to optimize the continuous size variables.
With the introduction of shape variables, the original optimization algorithm was improved in individual coding strategy as well as GA execution techniques.
Meanwhile, the update strategy of the first-level approximation problem was also improved.
The results of numerical examples show that the proposed method is effective in dealing with the three kinds of design variables simultaneously, and the required computational cost for structural analysis is quite small.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Shen-yan& Shui, Xiao-fang& Li, Dong-fang& Huang, Hai. 2015. Improved Genetic Algorithm with Two-Level Approximation for Truss Optimization by Using Discrete Shape Variables. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074038
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Shen-yan…[et al.]. Improved Genetic Algorithm with Two-Level Approximation for Truss Optimization by Using Discrete Shape Variables. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1074038
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Shen-yan& Shui, Xiao-fang& Li, Dong-fang& Huang, Hai. Improved Genetic Algorithm with Two-Level Approximation for Truss Optimization by Using Discrete Shape Variables. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1074038
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1074038
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر