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• W2183773222 abstract "As long as humankind exists, he tries to excel in all areas and will to the greatest degree of happiness with the least attempt. Evolution in human societies is not only based on personal experiences, but the condition of progress of any human society is based on preserving and applying the experiences and knowledge acquired from individuals in during different generations. These experiences would form culture of a population. The evolutionary algorithm, which uses the culture, would be known as cultural algorithm. One of the shortcomings of these algorithms is formation of a culture, and following of all people of the same culture that is trapping into involving in local optimums during evolution. To overcome this defect, many various algorithms have been applied. In this paper coincides with pareto ranking, a new method is introduced with the changes in functions and spaces of cultural algorithms such as production of some norm knowledge instead of knowledge, pay attention to not strong people with more improvement and multi-step promoting in ranking to other people, use some leaders to update the belief space and creating some modifications in influence function as any person in the population is influence under the nearest beliefs and culture. The results referred to the increase of convergence speed of new proposed method to its standard type." @default.
• W2183773222 created "2016-06-24" @default.
• W2183773222 creator A5038721504 @default.
• W2183773222 creator A5074799528 @default.
• W2183773222 date "2012-01-01" @default.
• W2183773222 modified "2023-09-27" @default.
• W2183773222 title "Towards Optimizing the Cultural Algorithms Performance" @default.
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