A New Testability Optimization Allocation Approach

Abstract:

This paper describes a methodology based on improved genetic algorithms (GA) and experiments plan to optimize the testability allocation. Test resources were reasonably configured for testability optimization allocation, in order to meet the testability allocation requirements and resource constraints. The optimal solution was not easy to solve of general genetic algorithm, and the initial parameter value was not easy to set up and other defects. So in order to more efficiently test and optimize the allocation, migration technology was introduced in the traditional genetic algorithm to optimize the iterative process, and initial parameters of algorithm could be adjusted by using AHP approach, consequently testability optimization allocation approach based on improved genetic algorithm was proposed. A numerical example is used to assess the method. and the examples show that this approach can quickly and efficiently to seek the optimal solution of testability optimization allocation problem.

• Periodical: Applied Mechanics and Materials (Volume 328)
• Pages: 444-449
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.328.444
• Online since: June 2013
• Authors: Gang Liu, Fang Li
• Keywords: Improved Genetic Algorithm (IGA), Optimization Allocation, Testability

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