Device test resource overall allocation method based on chaos genetic algorithm

Abstract

The invention discloses a device test resource overall allocation method based on a chaos genetic algorithm, and the method comprises the steps of determining an allocation optimization set according to a current test task requirement and a device resource condition, namely, determining a task / step set participating in allocation and an available device set participating in allocation; constructing a target function and a constraint condition; solving a mathematical model in the test resource overall allocation process by using the chaos genetic algorithm; constructing a chaotic crossover operator based on Logistic chaotic mapping, and generating a new individual by using the crossover probability of the chaotic genetic algorithm and the chaotic crossover operator; and forming a new generation of population by new individuals generated after chaos crossing and chaos variation until the chaos genetic algorithm converges, obtaining an optimal solution for test resource overall allocation, taking the optimal solution as a final allocation scheme of the device test resources, and outputting the allocation scheme. According to the invention, an existing mode of manual allocation of the device test resources is changed, and the problems of non-uniform allocation of the device test resources, low test efficiency and the like are solved.

Description

technical field [0001] The invention relates to the field of equipment testing, in particular to a method for coordinating and allocating equipment testing resources based on a chaotic genetic algorithm. Background technique [0002] Equipment testing is the assessment and verification of equipment performance, production conditions, and use conditions in accordance with the specified requirements during the equipment development process, with the purpose of ensuring that the performance and quality of the equipment meet the specified standards. For the completion of equipment test activities, different test subjects require different test resources to guarantee. Different test resources are distributed in different locations and units, and each test resource is isolated from each other. In the process of equipment test organization, facing different test requirements, it is often necessary for test personnel to use manual allocation and manual planning to complete the overa...

AI Technical Summary

Problems solved by technology

However, the standard genetic algorithm has problems such as premature convergence, large randomness in the generation of new individuals, and inability to obtain accurate solutions in the solution process.

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