Method for selecting leading particle of multi-target quantum particle swarm algorithm
A quantum particle swarm and multi-objective technology, which is applied in the field of selecting multi-objective quantum particle swarm algorithm leading particles, can solve the problems that the distribution is difficult to be uniform, and the Pareto front distribution of the multi-objective quantum particle swarm optimization algorithm is not uniform and sparse. , to achieve a uniform distribution
Inactive Publication Date: 2018-04-20
FUZHOU UNIV
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Such a leader particle selection mechanism will make it difficult to homogenize the distribution of the Pareto front, making the solutions where the solution density is high become denser, and the solutions where the solution density is low become sparser
[0003] The Pareto front distribution of the existing multi-objective quantum particle swarm optimization algorithm is not uniform enough, such as figure 1 Pareto Frontier of Multi-objective Quantum Particle Swarm Algorithm in Pareto Frontier, the existing way of randomly selecting leader particles needs to be improved
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[0027] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.
[0028] A method for selecting the leader particle of the multi-objective quantum particle swarm algorithm of the present invention, by straightening the Pareto front of the multi-objective quantum particle swarm algorithm, randomly selecting a coordinate in the straightened Pareto front of each section , and then select the solution closest to the coordinate as the leader particle to guide the search of the partition population, so that the corresponding particles in the part with higher solution density in the Pareto front have a low probability of being selected as the leader particle, and the solution density is low The particle corresponding to the position has a high probability of being selected as the leader particle, so that the Pareto frontier distribution is more uniform; the specific implementation steps of this method are as fo...
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The invention relates to a method for selecting a leading particle of a multi-target quantum particle swarm algorithm. The Pareto front of the multi-target quantum particle swarm algorithm is straightened in a segmented manner. A coordinate is randomly selected from each segment of the straightened Pareto front. Then a solution which is shortest to the coordinate is selected as the leading particle. Searching of the segmented population is guided so that the possibility of a fact that the corresponding particle in the part with relatively high solution density in the Pareto front is selected as the leading particle is low, and the possibility of a fact that the corresponding particle in the part with relatively low solution density is selected as the leading particle is high, thereby realizing higher distribution uniformity of the Pareto front. The method of the invention can realize higher distribution uniformity of the Pareto front.
Description
technical field [0001] The invention relates to the field of intelligent algorithm optimization, in particular to a method for selecting a leader particle of a multi-objective quantum particle swarm algorithm. Background technique [0002] Multi-objective optimization problems widely exist in daily production and life, but how to obtain an effective and comprehensive multi-objective Pareto front has always been a difficult point in multi-objective optimization problems. The quantum particle swarm optimization algorithm does not need to update the particle velocity, has the advantages of simple update formula, few setting parameters, and fast convergence speed, etc., and is widely used. However, in practical applications, there are defects that the Pareto front of the multi-objective quantum particle swarm optimization algorithm is unevenly distributed and not smooth, and it is difficult to search for the actual boundary of the Pareto front. Therefore, the existing improved ...
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IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 江岳文陈梅森
Owner FUZHOU UNIV