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Simple and efficient optimization method for improving artificial bee colony

An artificial bee colony optimization and high-efficiency technology, applied in artificial life, instruments, calculation models, etc., can solve problems that affect the application effect of algorithm engineering and large computational complexity, so as to improve the accuracy of optimization, clarify the physical meaning, and improve the solution effect of ability

Pending Publication Date: 2017-06-30
TIANJIN UNIV OF COMMERCE
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the improvement strategies of many algorithms increase the computational complexity while improving the global convergence ability and solution accuracy, which affects the actual engineering application effect of the algorithm.

Method used

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  • Simple and efficient optimization method for improving artificial bee colony
  • Simple and efficient optimization method for improving artificial bee colony
  • Simple and efficient optimization method for improving artificial bee colony

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Embodiment Construction

[0034] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0035] A kind of simple and efficient improved artificial bee colony optimization method that the technical scheme of the present invention proposes, comprises:

[0036] Select 8 mainstream Benchmark functions commonly used in bionic intelligent optimization algorithms f 1 ~ f 8 (As shown in Table 1); Table 1 is 8 kinds of mainstream Benchmark functions commonly used in bionic intelligent optimization algorithm testing;

[0037] Table 1

[0038]

[0039] The 8 functions in Table 1 include 2 Benchmark functions with dimension D=2, 2 Benchmark functions with D=30, 1 Benchmark function with D=60 and 3 Benchmark functions with D=100, each function has The theoretical mi...

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Abstract

The invention discloses a simple and efficient optimization method for improving an artificial bee colony. The method comprises the following steps of (1), initializing an algorithm; (2), calculating honey amount of each honey source according to an improved honey source initializing formula; (3), making bees search a new honey source according to a searching strategy based on normal distribution, and performing preferential selection on the new honey source and the old honey source; (4), calculating probability at each honey source position, and selecting a guiding bee for being followed by following bees according to the probability; (5), after number of searching times of one honey source reaches a cycling upper limit and updating does not occur, changing the guiding bee to a spy bee for searching; and (6), if a highest number of evolution generations is reached, outputting the position coordinate of an optimal honey source, and otherwise, returning to the step (3). According to the method of the invention, a normal distribution theory is introduced into an initializing process and a searching optimizing process of the artificial bee colony algorithm, thereby effectively improving global optimization solving capability and optimization precision.

Description

technical field [0001] The invention relates to the field of bionic intelligent optimization algorithms, in particular to a simple and efficient improved artificial bee colony optimization method. Background technique [0002] The artificial bee colony (ABC) algorithm is a new bionic intelligent optimization algorithm inspired by the behavior of honey bees. In the artificial bee colony algorithm, the bee colony is divided into three types: Employed bees, Onlooker bees and Scout bees. Among them, the leader bee and the follower bee each account for half of the NP of the population, and another role of scouting peak is set at the same time. The task of following bees is to complete the mining of honey sources, while the task of scout bees is to complete the exploration of high-quality honey sources. [0003] At present, in order to further improve the optimization solution ability of artificial bee colony algorithm, the improvement of artificial bee colony algorithm has beco...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 陈雷程学伟
Owner TIANJIN UNIV OF COMMERCE
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