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Constrained optimization algorithm based on decomposition-parallel genetic algorithm

A constrained optimization and genetic algorithm technology, applied in the direction of genetic laws, genetic models, complex mathematical operations, etc., can solve problems such as increased algorithm complexity and computing time

Inactive Publication Date: 2016-09-21
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Usually, the larger the scale, the more constraints will inevitably lead to a significant increase in algorithm complexity and calculation time

Method used

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  • Constrained optimization algorithm based on decomposition-parallel genetic algorithm
  • Constrained optimization algorithm based on decomposition-parallel genetic algorithm
  • Constrained optimization algorithm based on decomposition-parallel genetic algorithm

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Embodiment

[0053] In order to illustrate the technical effects of the present invention, a specific application example is used to verify the implementation of the present invention.

[0054] In the scientific research in the field of electronic system fault diagnosis, there is a multi-process measuring point selection problem. An electronic system to be tested often involves multiple test modules, and in the process of fault diagnosis of this system, in addition to meeting the overall testability index, the testability index of each module must also be met. Taking FDR as an example, its constraints can be expressed as:

[0055] F D R F D R ≥ FDR * FDR ...

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Abstract

The invention discloses a constrained optimization algorithm based on a decomposition-parallel genetic algorithm. A problem for the constrained optimization algorithm is decomposed into Q subproblems and one conventional problem; the obtained Q subproblems are decomposed by the adoption of the genetic algorithm at first and iterative evolution is carried out in parallel till at least more than one half chromosomes in a population corresponding to various subproblems satisfy constraint conditions of the subproblems; the chromosomes satisfying the constraint conditions are selected from the subproblems and form multiple chromosomes in sequence as an initial population of a conventional population; then, parallel genetic algorithm iteration of the conventional problem and the subproblems is carried out; when a migration interval is achieved, forward migration and backward migration are respectively carried out; and when a migration number is up to a threshold value, the optimal chromosome is selected from the population of the conventional problem and used as a solution of a constraint optimization problem. By the adoption of the decomposition-parallel genetic algorithm, the optimal or nearly optimization solution of the constraint optimization problem can be solved rapidly.

Description

technical field [0001] The invention belongs to the technical field of evolutionary algorithms, and more specifically relates to a constraint optimization algorithm based on decomposition-parallel genetic algorithm. Background technique [0002] The large-scale constrained optimization problem refers to solving the extremum of the objective function under multi-dimensional constraints, which is a common problem in the field of algorithm technology. Generally, it can be described as: finding minF under the conditions of the following inequalities objective (X): [0003] g i ( X ) ≤ 0 , i = 1 , 2 , ... , m ...

Claims

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Application Information

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IPC IPC(8): G06F17/12G06N3/12
CPCG06F17/12G06N3/126
Inventor 杨成林张贞周秀云
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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