مشاهده مشخصات مقاله
Local Promotion by Cellular Automata to Improve Genetic Search Strategy
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نویسنده (ها) |
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Behrouz Shahgholi Ghahfarokhi
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Mohammad Babaeizade
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Amir Hassan Monadjemi
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مربوط به کنفرانس |
دوازدهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
In recent years, optimization problems are considered as complex problems which require accurate and fast
search methods. Traditional search methods such as iterative search and evolutionary algorithms are not
efficient since they are not complete and their convergence rate is slow. A lot of efforts have been carried out to
improve the performance of genetic algorithms as a special class of evolutionary algorithms. The most
considerable ones are related to using the idea of cellular automata due to its nature of local operation. However,
a genetic cellular automaton considers the relationship between chromosomes, but sometimes is not efficient
enough due to the early convergence problem. Also, the tradeoff between fast convergence and optimum
exploration is unavoidable. In this paper, we propose a new genetic-based search method using cellular
automata. In this method, in contrast to the traditional genetic cellular automata, the transition rule of cellular
automata is utilized to promote the individuals before genetic operations have been accomplished globally. The
experimental results have shown better convergence rate and also exploration accuracy compared to the
traditional search methods. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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