An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems
المؤلفون المشاركون
Zhang, Zheng-Jiang
Peng, Wen-Wen
Dai, Yu-Xing
Zheng, Chong-Wei
Chen, Jie
Lu, Kang-Di
Zeng, Guo-Qiang
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-05-07
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
الملخص EN
As a novel evolutionary optimization method, extremal optimization (EO) has been successfully applied to a variety of combinatorial optimization problems.
However, the applications of EO in continuous optimization problems are relatively rare.
This paper proposes an improved real-coded population-based EO method (IRPEO) for continuous unconstrained optimization problems.
The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally.
The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA) versions with different mutation operations in terms of simplicity, effectiveness, and efficiency.
Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO), and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Zeng, Guo-Qiang& Lu, Kang-Di& Chen, Jie& Zhang, Zheng-Jiang& Dai, Yu-Xing& Peng, Wen-Wen…[et al.]. 2014. An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-470842
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Zeng, Guo-Qiang…[et al.]. An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems. Mathematical Problems in Engineering No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-470842
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Zeng, Guo-Qiang& Lu, Kang-Di& Chen, Jie& Zhang, Zheng-Jiang& Dai, Yu-Xing& Peng, Wen-Wen…[et al.]. An Improved Real-Coded Population-Based Extremal Optimization Method for Continuous Unconstrained Optimization Problems. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-470842
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-470842
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