Improved Frog Leaping Algorithm Using Cellular Learning Automata
محل انتشار: ماهنامه بین المللی مهندسی، دوره: 27، شماره: 1
سال انتشار: 1392
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 829
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شناسه ملی سند علمی:
JR_IJE-27-1_002
تاریخ نمایه سازی: 17 خرداد 1393
چکیده مقاله:
In this paper, a new algorithm which is the result of combination of cellular learning automata (CLA) and shuffled frog leap algorithm (SFLA) is proposed for optimization of functions in continuous, staticenvironments. In the frog leaping algorithm, every frog represents a feasible solution within theproblem space. In the proposed algorithm, each memeplex of frogs is placed in a cell of CLA. Learning automata in each cell acts as the brain of memeplex and will determine the strategy of motion and search.The proposed algorithm along with the standard SFLA and two global and local versions ofparticle swarm optimization algorithm have been tested in 30-dimensional space on five standard merit functions. Experimental results show that the proposed algorithm has a performance of the introduced algorithm is due to the control of search behavior of frogs during the optimization process
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نویسندگان
s Ranjkesh
Islamic Azad University, Roudsar-Amlash Branch, Iran