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A memetic animal migration optimizer for multimodal optimization

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Unimodal optimization algorithms can find only one global optimum solution, while multimodal ones have the ability to detect all/most existing local/global optima in the problem space. Many practical scientific and engineering optimization problems have multiple optima to be located. There are a considerable number of optimization approaches in the literature to address the unimodal problems. Although multimodal optimization methods have not been studied as much as the unimodal ones, they have attracted an enormous amount of attention recently. However, most of them suffer from a common nichin ...Daha fazlası

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Multi-circle Detection Using Multimodal Optimization

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Object and shape detection in digital image were one of the hot topic over the last two decades. Especially automatic multi circle detection has received more attention over last years. Hough transform (HT) is a well-known and most popular method for lines and circles detection. However, HT has huge computational complexity expense. This paper proposed a new successful heuristic method to reduce computation time and improve the speed of HT for circle detection. In this proposed method the edges information of the image is obtained by means of Robert edge detection. Then, multimodal particle sw ...Daha fazlası

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A multi-modal bacterial foraging optimization algorithm

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In recent years, multi-modal optimization algorithms have attracted considerable attention, largely because many real-world problems have more than one solution. Multi-modal optimization algorithms are able to find multiple local/global optima (solutions), while unimodal optimization algorithms only find a single global optimum (solution) among the set of the solutions. Niche-based multi-modal optimization approaches have been widely used for solving multi-modal problems. These methods require a predefined niching parameter but estimating the proper value of the niching parameter is challengin ...Daha fazlası

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