基于混沌算子增强遗传算法的资源统筹模型
A Resource Planning Model Based on Chaos Operator Enhanced Genetic Algorithm
孙晓 1李妍 1张昊 1赵颖2
作者信息
- 1. 军事科学院评估中心,北京 100091
- 2. 航天系统科学与工程研究院,北京 100037
- 折叠
摘要
面向复杂试验任务和多样性试验资源统筹调配需求,针对资源配置不均、效率低下等问题,基于试验资源统筹的业务流程,研究提出了一种基于混沌遗传算法的试验资源统筹方法.利用遗传算法建立试验资源统筹调配过程的数学模型,基于Logistic混沌映射构造混沌交叉算子和变异算子,并结合具体试验案例进行了算法设计实现和验证.算法避免了过早收敛、陷入局部最优等缺陷,能够快速实现试验资源优化配置,对于提高试验资源统筹利用的科学性具有积极作用.
Abstract
Aiming at the needs of complex experimental tasks and diverse experimental resource allocation,and addressing issues such as uneven resource allocation and low efficiency,a chaotic genetic algorithm based experimental resource allocation method is proposed based on the business process of experimental resource allocation.The mathematical model of experimental resources allocation process was established by using genetic algo-rithm,and the chaotic crossover operator and mutation operator were constructed based on Logistic chaotic mapping.The algorithm was designed,implemented and verified with a specific case,which avoids premature convergence,falling into local optimization and other defects,and can quickly realize the optimal allocation of test resources.The model plays a positive role in improving the scientificity of the overall utilization of test resources.
关键词
遗传算法/混沌算子/装备试验/资源统筹Key words
Genetic algorithm/Chaos operator/Equipment test/Resource planning引用本文复制引用
基金项目
国家自然科学基金(80904071)
国家自然科学基金(62106281)
出版年
2024
NETL
NSTL
万方数据