Construction of Mathematical Evaluation System Based on Improved Genetic Algorithm

The traditional mathematical evaluation system often faces problems such as large amount of calculation and unsatisfactory optimization effect. In the execution process of the algorithm, this paper adopts the adaptive crossover and mutation probability strategy, so that the algorithm can automatical...

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Bibliographic Details
Published in2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS) pp. 1 - 7
Main Author Lan, Lihong
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.08.2024
Subjects
elite retention strategy
Faces
Genetic algorithms
improved genetic algorithm
Indexes
mathematical evaluation system
Neural networks
Optimization
Particle swarm optimization
Robustness
Search problems
Simulated annealing
simulated annealing algorithm
Stability analysis
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Summary:The traditional mathematical evaluation system often faces problems such as large amount of calculation and unsatisfactory optimization effect. In the execution process of the algorithm, this paper adopts the adaptive crossover and mutation probability strategy, so that the algorithm can automatically adjust the search direction according to the evolutionary state to avoid falling into the local optimal solution. We design a multi-objective optimization mechanism, so that the algorithm can consider multiple evaluation indexes at the same time and realize the optimization of the comprehensive evaluation system. From the perspective of optimal solution quality, Improved Genetic Algorithm (IGA) outperforms Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithms in terms of average comprehensive score. This indicates that IGA can more effectively balance and optimize multiple factors and their sub indicators when constructing a mathematical evaluation system. In this paper, by integrating the improved genetic algorithm to construct a mathematical evaluation framework, we provide strong support for education, scientific research and decision support platforms.
DOI:10.1109/IACIS61494.2024.10721991