PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization
المؤلفون المشاركون
Chen, Shuangqing
Liu, Yang
Wei, Lixin
Guan, Bing
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-27، 27ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-02-20
دولة النشر
مصر
عدد الصفحات
27
التخصصات الرئيسية
الملخص EN
Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency.
However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks.
In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO.
In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity.
To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms.
Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Chen, Shuangqing& Liu, Yang& Wei, Lixin& Guan, Bing. 2018. PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-27.
https://search.emarefa.net/detail/BIM-1130791
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Chen, Shuangqing…[et al.]. PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-27.
https://search.emarefa.net/detail/BIM-1130791
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Chen, Shuangqing& Liu, Yang& Wei, Lixin& Guan, Bing. PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-27.
https://search.emarefa.net/detail/BIM-1130791
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130791
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