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Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects
المؤلفون المشاركون
Houtinezhad, Maryam
Ghaffari, Hamid Rida
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 18، العدد 3 (31 مايو/أيار 2021)، ص ص. 261-269، 9ص.
الناشر
جامعة الزرقاء عمادة البحث العلمي
تاريخ النشر
2021-05-31
دولة النشر
الأردن
عدد الصفحات
9
التخصصات الرئيسية
العلوم الاقتصادية والمالية وإدارة الأعمال
الملخص EN
The goal of optimizing the best acceptable answer is according to the limitations and needs of the problem.
For a problem, there are several different answers that are defined to compare them and select an optimal answer; a function is called a target function.
The choice of this function depends on the nature of the problem.
Sometimes several goals are together optimized; such optimization problems are called multi-objective issues.
One way to deal with such problems is to form a new objective function in the form of a linear combination of the main objective functions.
In the proposed approach, in order to increase the ability to discover new position in the Imperialist Competitive Algorithm (ICA), its operators are combined with the particle swarm optimization.
The colonial competition optimization algorithm has the ability to search global and has a fast convergence rate, and the particle swarm algorithm added to it increases the accuracy of searches.
Inthis approach, the cosine similarity of the neighboring countries is measured by the nearest colonies of an imperialist and closest competitor country.
In the proposed method, by balancing the global and local search, a method for improving the performance of the two algorithms is presented.
The simulation results of the combined algorithm have been evaluated with some of the benchmark functions.
Comparison of the results has been evaluated with respect to metaheuristic algorithms suchm as Differential Evolution (DE), Ant Lion Optimizer (ALO), ICA, Particle Swarm Optimization (PSO), and Genetic Algorithm (GA).
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Houtinezhad, Maryam& Ghaffari, Hamid Rida. 2021. Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects. The International Arab Journal of Information Technology،Vol. 18, no. 3, pp.261-269.
https://search.emarefa.net/detail/BIM-1432093
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Houtinezhad, Maryam& Ghaffari, Hamid Rida. Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects. The International Arab Journal of Information Technology Vol. 18, no. 3 (May. 2021), pp.261-269.
https://search.emarefa.net/detail/BIM-1432093
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Houtinezhad, Maryam& Ghaffari, Hamid Rida. Improvement of imperialist competitive algorithm based on the cosine similarity criterion of neighboring objects. The International Arab Journal of Information Technology. 2021. Vol. 18, no. 3, pp.261-269.
https://search.emarefa.net/detail/BIM-1432093
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 276-179
رقم السجل
BIM-1432093
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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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
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