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Optimization calculation method based on improved adaptive quantum particle swarm optimization algorithm

A quantum particle swarm, optimization computing technology, applied in computing, computing models, instruments, etc., can solve problems such as the inability to find the optimal solution, and achieve the effect of improving the ability of global optimization

Inactive Publication Date: 2018-10-02
HARBIN ENG UNIV
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Problems solved by technology

[0012] The purpose of the present invention is to provide an improved adaptive algorithm based on the improved inertia weight that can determine the corresponding inertia weight according to the different search states of each particle for the problem that the linear reduction of the inertia weight in the traditional QPSO algorithm can not finally find the optimal solution. Optimal Computing Method of Quantum Particle Swarm Algorithm

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  • Optimization calculation method based on improved adaptive quantum particle swarm optimization algorithm
  • Optimization calculation method based on improved adaptive quantum particle swarm optimization algorithm
  • Optimization calculation method based on improved adaptive quantum particle swarm optimization algorithm

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Embodiment Construction

[0048] The present invention is described in more detail below in conjunction with accompanying drawing example:

[0049] to combine Figure 1-4 , the present invention is an adaptive quantum particle swarm optimization (AQPSO) method that can determine corresponding inertia weights for different search states of each particle. The technical solution adopted by the present invention is to establish a suitable evaluation index according to the needs, distinguish the optimization degree of each particle, and assign different inertia weights according to the optimization state of each particle, which can be realized according to the following steps:

[0050] Step 1: According to the actual optimization problem, establish the objective function to be optimized.

[0051] Step 2: Initialize various parameters required by the optimization algorithm, including population size, problem dimension, maximum number of iterations, and range of inertial weights.

[0052] Step 3: Randomly g...

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Abstract

The invention aims to provide an optimization calculation method based on an improved adaptive quantum particle swarm optimization algorithm. The technical scheme adopted by the invention is that appropriate evaluation indexes are established according to requirements, the optimization degree of each particle is distinguished, and different inertia weights are automatically distributed according to the optimization state of each particle. The optimization calculation method solve adjustment problems single control parameter and single inertia weight linear decrease in the traditional QPSO (Quantum Particle Swarm Optimization) algorithm. The global optimization ability of the algorithm can be effectively improved through adjusting the inertia weights of particles with different optimizationdegrees in a targeted manner.

Description

technical field [0001] The invention relates to an optimization calculation method for solving high-dimensional problems. Background technique [0002] Due to the good practicability of optimization technology, it has been widely used in various engineering fields. The purpose of optimization is to obtain the best solution from a large number of optimization strategies, to determine the characteristics of the optimal point of the objective function in the domain and the corresponding solution method. Using an optimization algorithm to solve a problem can be defined as finding a series of appropriate system parameters under certain constraints to ensure that the entire system can obtain the maximum or minimum output or performance index. [0003] The Optimization Problem is defined as follows: [0004] [0005] In the formula, S is the solution space, which is a non-empty set, representing the entire optimized search space; f(x) represents the objective function correspo...

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Application Information

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IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 王宏健周赫雄袁建亚李庆王莹张宏瀚
Owner HARBIN ENG UNIV
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