具有约束的规范混料模型最优设计  

Optimal design of standard mixture model with constraints

作　　者：苏晴 张崇岐 SU Qing;ZHANG Chong-qi(School of Economics and Statistics,Guangzhou University,Guangzhou 510006,China)

机构地区：[1]广州大学经济与统计学院,广东广州510006

出　　处：《广州大学学报（自然科学版）》2020年第6期58-63,共6页Journal of Guangzhou University:Natural Science Edition

基　　金：国家自然科学基金资助项目(12071096)。

摘　　要：求解最优的混料模型是实际应用中常见的问题.较传统的求最优混料模型的一般方法,遗传算法在避免局部最优解的情况下可以更有效地求得全局较精确最优解.文章基于遗传算法,在混料试验数据下获得煤矿石、壤土和沙石的最优设计,以此解释并说明运用遗传算法求解最优设计的混料模型的步骤.It is commonplace to solve the optimal mixture model in practical applications.Compared with the conventional methods in finding the optimal mixture model,genetic algorithm is more effective in finding a more accurate global optimal solution while avoiding the local optimal solution.Based on a genetic algorithm,the optimization of the coal mine,loam,and sand are obtained under mixing test,and this paper explains and illustrates the steps of using the genetic algorithm to solve the optimal mixture model.

关 键 词：混料模型 遗传算法 最优设计 

分 类 号：O212.6[理学—概率论与数理统计]