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Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems
المؤلفون المشاركون
Wang, Jiquan
Ersoy, Okan K.
Cheng, Zhiwen
Zhang, Panli
Dai, Weiting
Dong, Zhigui
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-06-06
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
An improved real-coded genetic algorithm (IRCGA) is proposed to solve constrained optimization problems.
First, a sorting grouping selection method is given with the advantage of easy realization and not needing to calculate the fitness value.
Secondly, a heuristic normal distribution crossover (HNDX) operator is proposed.
It can guarantee the cross-generated offsprings to locate closer to the better one among the two parents and the crossover direction to be very close to the optimal crossover direction or to be consistent with the optimal crossover direction.
In this way, HNDX can ensure that there is a great chance of generating better offsprings.
Thirdly, since the GA in the existing literature has many iterations, the same individuals are likely to appear in the population, thereby making the diversity of the population worse.
In IRCGA, substitution operation is added after the crossover operation so that the population does not have the same individuals, and the diversity of the population is rich, thereby helping avoid premature convergence.
Finally, aiming at the shortcoming of a single mutation operator which cannot simultaneously take into account local search and global search, this paper proposes a combinational mutation method, which makes the mutation operation take into account both local search and global search.
The computational results with nine examples show that the IRCGA has fast convergence speed.
As an example application, the optimization model of the steering mechanism of vehicles is formulated and the IRCGA is used to optimize the parameters of the steering trapezoidal mechanism of three vehicle types, with better results than the other methods used.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Jiquan& Cheng, Zhiwen& Ersoy, Okan K.& Zhang, Panli& Dai, Weiting& Dong, Zhigui. 2018. Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems. Mathematical Problems in Engineering،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1208066
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Jiquan…[et al.]. Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems. Mathematical Problems in Engineering No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1208066
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Jiquan& Cheng, Zhiwen& Ersoy, Okan K.& Zhang, Panli& Dai, Weiting& Dong, Zhigui. Improvement Analysis and Application of Real-Coded Genetic Algorithm for Solving Constrained Optimization Problems. Mathematical Problems in Engineering. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1208066
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1208066
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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