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An Adaptive Pigeon Swarm Optimization Method Based on Improved Multi-population Global Optimum

A pigeon swarm optimization and global optimal technology, applied in instruments, artificial life, computing, etc., can solve the problem of particle swarm optimization falling into local optimum, and achieve the effect of improving quality and performance

Active Publication Date: 2022-02-15
BEIJING UNIV OF TECH
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  • Application Information

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Problems solved by technology

[0005] In order to solve the multi-objective problem of parameter adjustment in the modern industrial process, the present invention provides an adaptive pigeon group optimization method based on improved multi-population global optimization
Solve the problem that the particle swarm algorithm is easy to fall into local optimum

Method used

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  • An Adaptive Pigeon Swarm Optimization Method Based on Improved Multi-population Global Optimum
  • An Adaptive Pigeon Swarm Optimization Method Based on Improved Multi-population Global Optimum
  • An Adaptive Pigeon Swarm Optimization Method Based on Improved Multi-population Global Optimum

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Embodiment Construction

[0060] The method proposed in this paper can solve the multi-objective problem of parameter tuning in industrial processes. By composing the parameter values ​​to be adjusted into a vector, this vector is called a particle. Through the random flight of particle swarms (that is, a large number of particles) to efficiently solve the optimal value of industrial process parameter settings.

[0061] The effectiveness of the method will be tested with ZDT problems. First, introduce the ZDT problem. The ZDT problem is a general term for a variety of objective function pairs. Table 1 lists the characteristics, dimensions and simple dimensions of the Pareto true front for each ZDT instance. Each ZDT problem has a pair of objective functions, and the ultimate goal of the problem is to minimize (or maximize) the output values ​​of the two functions as much as possible. However, the reduction of the output value of one function in the ZDT problem usually leads to the increase of the ou...

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Abstract

The invention discloses an adaptive pigeon group optimization method based on improved multi-population global optimization. The present invention includes two stages of "particle convergence stage" and "particle diversity stage". "Particle convergence stage" firstly projects the particles, obtains the individual and global information of the particles, and selects the global optimal convergence; then uses the speed and position update formula to adjust the particles; finally archives the particles and iterates in a loop. The "particle diversity stage" includes: projecting the particles, obtaining the individual and global information of the particles, and selecting the global optimal diversity; then adjusting the particles using the position update formula; finally archiving the particles and looping iterations. The present invention considers the convergence or diversity of solutions respectively, and finally obtains a multi-objective problem solving method with excellent performance.

Description

technical field [0001] The invention belongs to the technical field of multi-objective problem optimization, in particular to a multi-objective particle swarm global optimization technology in the modern industrial field. The method based on pigeon group optimization of the present invention is a specific application in a typical multi-objective optimization problem——ZDT problem (Zitzler-Deb-Thiele's function). Background technique [0002] The modern industrial process is a complex system, and its process data has the characteristics of dynamic, nonlinear and multi-constraint. In order to improve the efficiency of industrial production process and reduce the occurrence of accidents, multi-objective optimization methods have received extensive attention. The multi-objective evolutionary algorithm has a good global exploration ability, and does not need to understand the mathematical model of the problem. Because of its simplicity and high efficiency, the multi-objective ev...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 常鹏卢瑞炜张祥宇王普
Owner BEIJING UNIV OF TECH