A novel differential evolution algorithm
A differential evolution algorithm and differential evolution technology, applied in the fields of science and engineering, can solve the problems of premature convergence, time-consuming genetic algorithm, poor local search ability of genetic algorithm, etc., to improve the convergence speed, improve local search ability, and avoid premature convergence. effect of the problem
Inactive Publication Date: 2019-03-01
SUN YAT SEN UNIV
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Problems solved by technology
[0008] The local search ability of the genetic algorithm is poor, resulting in a time-consuming simple genetic algorithm, and the search efficiency is low in the later stage of evolution
And in practical applications, the genetic algorithm is prone to premature convergence problems
Since the offspring of the differential evolution algorithm are directly generated from the parent, as the evolutionary algebra increases, the differences between individuals will gradually decrease, resulting in premature convergence to the vicinity of the local extremum, forming a premature convergence phenomenon
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[0019] The accompanying drawings are for illustrative purposes only, and should not be construed as limitations on this patent; in order to better illustrate this embodiment, certain components in the accompanying drawings will be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art It is understandable that some well-known structures and descriptions thereof may be omitted in the drawings. The positional relationship described in the drawings is for illustrative purposes only, and should not be construed as a limitation on this patent.
[0020] Such as figure 1 As shown, a new type of differential evolution algorithm, which includes the following steps:
[0021] S1. Randomly generate a population P with an initial population size of N, and output the population P;
[0022] S2. Name the input population P, perform differential evolution operation on population P, and generate a new population Q with a population size...
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The present invention relates to the technical field of science and engineering, and more particularly, to a novel differential evolution algorithm. The invention provides a novel differential evolutionary algorithm, which improves the local search ability of the evolutionary algorithm because the descendants are directly generated by the excellent parent generation, avoids the premature convergence problem of the differential algorithm by controlling the direction of the evolutionary center point of the descendant generation, and effectively improves the convergence speed of the genetic algorithm by the invention.
Description
technical field [0001] The present invention relates to the technical field of science and engineering, and more specifically, relates to a novel differential evolution algorithm. Background technique [0002] The traditional genetic algorithm generates new solutions by simulating the cross-mutation of organisms. This method has a certain degree of randomness, may not be able to converge to the global optimum, and has a low search rate. Differential evolution algorithm is an efficient heuristic parallel search technology, but the standard differential evolution algorithm is easy to cause premature convergence of population individuals. [0003] Evolutionary algorithm is a series of search techniques based on the basic calculation model of natural evolution process, which has been widely used in many fields such as function optimization, pattern recognition, machine learning, neural network training, intelligent control and so on. [0004] The realization process of evolutio...
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Login to View More IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 周育人邓瑶
Owner SUN YAT SEN UNIV