Multi-target particle swarm optimization algorithm based on ASU strategy

A multi-objective particle swarm, optimization algorithm technology, applied in computing, genetic models, instruments, etc., can solve the problem of inapplicable high-dimensional models, lack of regional particles, and can not well maintain the diversity of solutions and the uniformity of distribution, etc. problems to achieve the effect of maintaining uniformity and diversity, improving reliability, and improving uniformity and diversity

Inactive Publication Date: 2014-06-11
STATE GRID CORP OF CHINA +2
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Problems solved by technology

At present, the decision-making problem of power transmission and transformation projects is often established as a multi-objective optimization model. When using the traditional method based on the crowding distance strategy to solve it, all particles smaller than a certain distance are eliminated at one time, resulting in the lack of particles in some areas, and not It is suitable for high-dimensional models; when using the method based on the grid strategy, there will be the disadvantage that two very similar non-dominated solutions are divided into two adjacent grids and remain in the solution set
It can be seen that the traditional method cannot well maintain the diversity of solutions and the uniformity of distribution, resulting in the final result being not optimal

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  • Multi-target particle swarm optimization algorithm based on ASU strategy
  • Multi-target particle swarm optimization algorithm based on ASU strategy
  • Multi-target particle swarm optimization algorithm based on ASU strategy

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Embodiment Construction

[0026] The present invention will be described in detail below in conjunction with accompanying drawing and embodiment: figure 1 As shown, the multi-objective particle swarm optimization algorithm based on the ASU strategy of the present invention comprises the following steps:

[0027] (1) Population initialization. Set the elite set to be empty; the number of iterations t=0, within the range of control variables, randomly initialize the particle swarm, the individual extremum and the global extremum of each particle are the initial positions, and set the scale of the elite set;

[0028] (2) Calculate the fitness value of the objective function of each particle;

[0029] (3) Judging whether the end criterion is met, the maximum allowable number of iterations is reached or the value of the objective function corresponding to the optimal solution changes less than a given value within a given number of iteration steps, stop optimization and output the result to form a Pareto o...

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Abstract

The invention relates to a multi-target particle swarm optimization algorithm based on an ASU strategy. According to the multi-target particle swarm optimization algorithm, elitism set reduction is carried out based on the ASU strategy, the uniformity and the diversity of optimal solution distribution can be improved, a relatively-superior solution can be searched, and the reliability of final results is accordingly improved. As for multi-target optimization, in the elitism set reduction process, a particle swarm is divided into a plurality of grids, the gradually-updated Euclidean crowding distance is adopted for screening particles in each grid, the diversity and the uniformity of solution distribution are prevented from being damaged by removing the particles in a swarm set at a time, and the relatively-superior solution can be searched.

Description

technical field [0001] The invention relates to a multi-objective particle swarm optimization algorithm based on ASU (Asynchronous-Stepwise Updated) strategy, which belongs to the technical field of power system planning. Background technique [0002] With the rapid development of my country's economy and the continuous expansion of the power system, people's requirements for the safety, reliability, and quality of power supply are also increasing. It is bound to require a large number of power transmission and transformation projects to be invested in the construction of the power grid. In response to the demand for power grid construction, a large number of power transmission and transformation projects are reported every year. Some of these projects are needed for power grid construction, and they can solve a certain defect of the power grid, but the other part is unnecessary, or the reported scheme is not optimal, and needs to be replaced with a better implementation sch...

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06N3/12
Inventor 孙可郑朝明丁晓宇陈宏伟宁康红徐凯江全元邹杨郑晓赵萌
Owner STATE GRID CORP OF CHINA
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