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Hybrid particle swarm optimization algorithm in combination with genetic algorithm

A hybrid particle swarm and particle swarm optimization technology, applied in the field of optimization technology research, can solve problems such as poor optimization effect

Inactive Publication Date: 2018-08-14
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to propose a hybrid particle swarm optimization algorithm combined with a genetic algorithm for the problem that the traditional optimization algorithm has a poor optimization effect when solving complex optimization problems

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  • Hybrid particle swarm optimization algorithm in combination with genetic algorithm
  • Hybrid particle swarm optimization algorithm in combination with genetic algorithm
  • Hybrid particle swarm optimization algorithm in combination with genetic algorithm

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Embodiment Construction

[0057] Now in conjunction with embodiment, accompanying drawing, the present invention will be further described:

[0058] A hybrid particle swarm optimization algorithm combined with a genetic algorithm, the hybrid optimization algorithm combines the advantages of strong global search capabilities of the particle swarm optimization (Particle Swarm Optimization, PSO) algorithm and fast local convergence speed of the genetic algorithm (Genetic Algorithm, GA), First, the global search is carried out with the help of the strong global search ability of the particle swarm optimization algorithm. When the number of iterations reaches the specified algebra and is close to the global optimal solution, the entire population enters the neighborhood of the global optimal solution; secondly, the improved genetic The algorithm performs a local fast search in the neighborhood of the global optimal solution, and finally reaches the global optimal solution.

[0059] Step 1: Describe the gene...

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Abstract

The invention discloses a hybrid particle swarm optimization algorithm in combination with a genetic algorithm. The advantages of strong global search capability of a particle swarm optimization (PSO)algorithm and high local convergence speed of the genetic algorithm (GA) are integrated. Firstly, global search is performed by virtue of the characteristic of the strong global search capability ofthe PSO algorithm, and when iteration is performed for a specified algebra and is close to a globally optimal solution, at the moment, a whole population enters a neighborhood of the globally optimalsolution; and secondly, local quick search is performed in the neighborhood of the globally optimal solution by utilizing an improved genetic algorithm, so that the globally optimal solution is reached finally.

Description

technical field [0001] The invention belongs to the field of optimization technology research. In particular, it involves complex optimization problems with multiple control variables, multiple constraints, and the objective function to be optimized has multiple extreme points. The hybrid optimization algorithm can be widely used to solve various engineering and theoretical optimization problems. Background technique [0002] Optimization problems generally exist in various fields of industrial production (including military and civilian), and the research on optimization problems has enormous potential application value. The optimization problem refers to finding the appropriate control variables under specific constraints so that the objective function to be optimized takes the maximum or minimum value. Therefore, the key to solving the optimization problem is to design an optimization algorithm that can quickly and accurately find the control variables that meet the con...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00G06N3/12G06Q10/04
CPCG06N3/006G06N3/126G06Q10/04
Inventor 张栋曹林
Owner NORTHWESTERN POLYTECHNICAL UNIV
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