Grouping-comprehensive multi-objective evolutionary-based multi-task test optimization method

A multi-objective evolution and multi-task technology, applied in the multi-task testing optimization field based on grouping-integrated multi-objective evolution, can solve the problems of many objects, unfavorable search solutions and high dimension.

Inactive Publication Date: 2017-06-23
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

Then, for the multi-task test optimization problem, if the overall optimization objective and the single-task optimization objective are simply integrated together, and the multi-objective evolutionary al

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  • Grouping-comprehensive multi-objective evolutionary-based multi-task test optimization method
  • Grouping-comprehensive multi-objective evolutionary-based multi-task test optimization method

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Embodiment

[0027] According to the characteristics of multi-task test optimization, the present invention adopts grouping-integrated multi-objective evolution to realize multi-task test optimization. figure 1 It is a specific implementation flow chart of the multi-task test optimization method based on grouping-integrated multi-objective evolution of the present invention. Such as figure 1 Shown, the concrete steps of the multi-task test optimization method based on grouping-comprehensive multi-objective evolution of the present invention include:

[0028] S101: Obtain system-related data:

[0029] Obtain the multi-task test dependency matrix of the system according to the system information, select the preferred reference testability indicators of the multi-task test according to the actual needs, including the fault detection rate or fault isolation rate, and determine the evolution of the overall system and each testability index in each task mode objectives, and constraints on the ...

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Abstract

The invention discloses a grouping-comprehensive multi-objective evolutionary-based multi-task test optimization method. The method comprises the steps of firstly adopting a multi-objective evolutionary algorithm for each task mode to obtain an elite individual set of test optimization, wherein individuals in the multi-objective evolutionary algorithm are test scheme selection vectors, evolutionary objectives are preset evolutionary objectives of a testability index in the task modes, and a constraint condition of each evolutionary objective is a constraint condition of the testability index in the corresponding task mode; secondly performing multi-task comprehensive test optimization by adopting the multi-objective evolutionary algorithm according to the elite individual set of each task mode, wherein elements of the individuals are serial numbers of the elite individuals of each task mode in the corresponding set; and according to the obtained elite individual set, obtaining multi-task test scheme selection vectors, namely, non-dominated solutions of the multi-task test optimization. By adopting the method, the non-dominated solutions of the multi-task test optimization under the multi-objective condition can be obtained more quickly, and a calculation result is more accurate.

Description

technical field [0001] The invention belongs to the technical field of system fault diagnosis, and more specifically relates to a multi-task test optimization method based on grouping-integrated multi-objective evolution. Background technique [0002] With the development of semiconductor integrated circuits in the direction of integration and miniaturization, electronic systems are becoming more and more complex, and it is becoming more and more inconvenient to set measuring points in the circuit. Due to the sharp reduction of measuring points, fault diagnosis is more difficult. The situation of inversion of development cost and maintenance cost often occurs, which increases the number of maintenance personnel, requires higher technical levels for them, and lengthens training time. In order to reduce the difficulty of maintaining equipment in the future, testability design should be considered in the initial stage of system design. Testability refers to the degree to which...

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Application Information

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IPC IPC(8): G06F11/07
CPCG06F11/0751
Inventor 杨成林何安东
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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