An Improved Hybrid Algorithm Based on BiogeographyComplex and Metropolis for Many-Objective Optimization
المؤلفون المشاركون
Wang, Chen
Wang, Yi
Wang, Kesheng
Dong, Yao
Yang, Yang
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-03-30
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
It is extremely important to maintain balance between convergence and diversity for many-objective evolutionary algorithms.
Usually, original BBO algorithm can guarantee convergence to the optimal solution given enough generations, and the Biogeography/Complex (BBO/Complex) algorithm uses within-subsystem migration and cross-subsystem migration to preserve the convergence and diversity of the population.
However, as the number of objectives increases, the performance of the algorithm decreases significantly.
In this paper, a novel method to solve the many-objective optimization is called Hmp/BBO (Hybrid Metropolis Biogeography/Complex Based Optimization).
The new decomposition method is adopted and the PBI function is put in place to improve the performance of the solution.
On the within-subsystem migration the inferior migrated islands will not be chosen unless they pass the Metropolis criterion.
With this restriction, a uniform distribution Pareto set can be obtained.
In addition, through the above-mentioned method, algorithm running time is kept effectively.
Experimental results on benchmark functions demonstrate the superiority of the proposed algorithm in comparison with five state-of-the-art designs in terms of both solutions to convergence and diversity.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Chen& Wang, Yi& Wang, Kesheng& Dong, Yao& Yang, Yang. 2017. An Improved Hybrid Algorithm Based on BiogeographyComplex and Metropolis for Many-Objective Optimization. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1189838
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Chen…[et al.]. An Improved Hybrid Algorithm Based on BiogeographyComplex and Metropolis for Many-Objective Optimization. Mathematical Problems in Engineering No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1189838
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Chen& Wang, Yi& Wang, Kesheng& Dong, Yao& Yang, Yang. An Improved Hybrid Algorithm Based on BiogeographyComplex and Metropolis for Many-Objective Optimization. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1189838
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1189838
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