دانلود رایگان مقاله بررسی جامع الگوریتم کریل گله (KH) و کاربردهای آن

عنوان فارسی
بررسی جامع: الگوریتم کریل گله (KH) و کاربردهای آن
عنوان انگلیسی
A comprehensive review: Krill Herd algorithm (KH) and its applications
صفحات مقاله فارسی
0
صفحات مقاله انگلیسی
10
سال انتشار
2016
نشریه
الزویر - Elsevier
فرمت مقاله انگلیسی
PDF
کد محصول
E2160
رشته های مرتبط با این مقاله
مهندسی کامپیوتر و مهندسی فناوری اطلاعات
گرایش های مرتبط با این مقاله
مهندسی الگوریتم ها و محاسبات
مجله
محاسبات کاربردی نرم - Applied Soft Computing
دانشگاه
گروه علوم کامپیوتر، دانشکده علوم محض و کاربردی، دانشگاه Wukari، نیجریه
کلمات کلیدی
الگوریتم کریل گله، الگوریتم های هوش ازدحامی، الگوریتم های الهام گرفته از طبیعت، الگوریتمهای فراابتکاری
۰.۰ (بدون امتیاز)
امتیاز دهید
چکیده

ABSTRACT


 Krill Herd (KH) algorithm is a class of nature-inspired algorithm, which simulates the herding behavior of krill individuals. It has been successfully utilized to tackle many optimization problems in different domains and found to be very efficient. As a result, the studies has expanded significantly in the last 3 years. This paper presents the extensive (not exhaustive) review of KH algorithm in the area of applications, modifications, and hybridizations across these fields. The description of how KH algorithm was used in the approaches for solving these kinds of problems and further research directions are also discussed.

نتیجه گیری

8. Discussion and conclusion


This section summarizes the review of the studies on KH algorithm as given in Tables 1–3 where the publications related to the KH algorithm in terms of various areas of application, modification and hybridization to different formulations of combinatorial optimization problems are studied. Based on these tables, it can be seen that, the growth of this algorithm is on the increasing, despite the fact that its proposition is about three years. In accordance to the reviewed articles, it can be observed that the burk of the study on this algorithm focused on algorithmic applications and modifications to several area of discipline, yet there is still much more to do in this direction. Further studies of this algorithm in terms of its adaptation to other domain, self-adaptation of control parameters and theoretical studies needs to be investigated in the nearest future. Literature have shown that no much works have been carried out on theoretical aspect of the KH algorithm in general, it would be interesting to perform a theoretical study of the run-time and convergence properties ofthis algorithmas well asfitness landscapes and its dynamics nature. The design of parameter-less KH algorithmwhere there will benoparameters to be tuned by theuser and population structured of the KH algorithm are another aspect theoretical research area that worth investigating. Finally, forces on krill are overwhelming in nature, therefore, effects of other environmental factors such as water/ocean speed,tides and turbulence, etc., which may often larger than the speed of individual krill in the KH algorithm needs further investigation to improve the search process of the original KH algorithm.


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