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We introduce weighted moving vectors to increase the accuracy of estimating a convergence point of population and evaluate its efficiency. Key point is to weight moving vectors according to their reli...ability when a convergence point is calculated instead of equal weighting of the original method. We propose two different methods to evaluate the reliability of moving vectors. The first approach uses the fitness gradient information between starting points and terminal points of moving vectors for their weights. When a fitness gradient is bigger, the direction of a moving vector may have more potential, and a higher weight is given to it. The second one uses the fitness of parents, i.e. starting points of moving vectors, to give weights for moving vectors. Because an individual with higher fitness may have a high probability of being close to the optimal area, it should be given a higher weight, vice versa. If the estimated point is better than the worst続きを見る
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Mendeley出力
Yu2019_Article_AcceleratingEvolutionaryComput