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The problem of the multi- constrained concurrent optimization is a difficult artificial intelligence one that exists widely in the real life and confuses humans for years. Such as: the operating frequency of planes and trains, the course arrangement in school and the test paper grouping etc. This paper adopts the improved genetic algorithm, takes the test paper grouping problem for example, and puts forward a solution to the multi-constrained concurrent optimization problem. Finally, the paper aims to confirm the feasibility of this program through the experimental data.

The Research and Solutions to the Multi-constrained Concurrent Optimization Problem in Automatic Test Paper Tasks