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

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。

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.