Bionic strategy optimized hybrid whale optimization algorithm

A whale and algorithm technology, applied in the field of hybrid whale algorithm, can solve problems such as not easy to jump out of local minimum, lack of global search, etc., to avoid premature convergence problems, uniform initial position distribution, and enhance performance

Inactive Publication Date: 2017-08-04
ZHEJIANG UNIV
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Problems solved by technology

The standard whale algorithm can achieve fast convergence based on group optimization, but it will be deficient in global search. Therefore, it will fall into a local convergence trap in the optimization of function extreme values ​​with multi-peak characteristics, and it is difficult to jump out of local minima.

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  • Bionic strategy optimized hybrid whale optimization algorithm
  • Bionic strategy optimized hybrid whale optimization algorithm
  • Bionic strategy optimized hybrid whale optimization algorithm

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Embodiment Construction

[0016] Below according to accompanying drawing of description, in conjunction with specific embodiment, the present invention is further described:

[0017] A hybrid whale algorithm optimized by a bionic strategy. The algorithm uses Chebyshev chaotic mapping to realize the population initialization of the whale group. During the search process, a new mathematical model is used to update the position of the individual, so that the convergence performance of the algorithm is optimized, and the early stage is avoided. Premature convergence problems are conducive to jumping out of the local convergence trap.

[0018] A hybrid whale algorithm for bionic strategy optimization, which mainly has the following steps to realize:

[0019] Step 1: Use the Chebyshev chaotic map to realize the population initialization of the whale group;

[0020] Step 2: During the search process, the position of the individual whale is updated according to the mathematical model formula (1) and formula (...

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Abstract

The invention discloses a hybrid whale algorithm optimized by a bionic strategy. The algorithm uses Chebyshev chaotic mapping to realize the population initialization of the whale group, and uses a new mathematical model to update the individual position during the search process, so that the convergence performance of the algorithm is optimized. . The hybrid whale algorithm optimized by a bionic strategy of the present invention is beneficial to avoid the pre-mature convergence problem of general optimization algorithms, and is conducive to jumping out of the local convergence trap.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a hybrid whale algorithm for bionic strategy optimization. Background technique [0002] The standard whale optimization algorithm (Whale optimization algorithm, WOA) is a crowd intelligence algorithm proposed by Mirjalili and Lewis in 2016. It is an optimization algorithm implemented by imitating the predation behavior mechanism of humpback whales. The standard whale algorithm can achieve fast convergence based on group optimization, but it will be deficient in global search. Therefore, it will fall into a local convergence trap in the optimization of function extreme values ​​with multi-peak characteristics, and it is difficult to jump out of local minima. . Contents of the invention [0003] The technical problem to be solved by the present invention is to propose a hybrid whale algorithm with bionic strategy optimization aiming at the shortcoming that the standard wh...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 沈海斌巩世兵张尧
Owner ZHEJIANG UNIV
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