基于遗传算法的工业炸药仓储优化研究与仿真  

Study and Simulation of Storage Optimization of Industrial Explosives Based on Genetic Algorithm

作　　者：徐钒诚 谌海云[1] 杨帅东 李洋[1] XU Fan-cheng;CHEN Hai-yun;YANG Shuai-dong;LI Yang(Southwest Petroleum University,Chengdu Sichuan 610500,China)

机构地区：[1]西南石油大学,四川成都610500

出　　处：《计算机仿真》2023年第7期501-508,共8页Computer Simulation

基　　金：南充市市校合作项目(21SXHZ0011);南充市市校合作项目(21SXHZ0012)。

摘　　要：针对工业炸药仓储优化问题,对工业炸药仓储管理的实际难点和需求进行分析,提出工业炸药存储方案并建立数学优化模型。并根据遗传算法求解仓储模型过程中存在的问题,提出一种基于信息熵及改进的自适应变异算子的混合遗传算法,对所提模型求解。仿真结果表明,上述算法对所提模型求解在收敛精度及速度上均取得良好效果,同时提高了工业炸药仓库群的空间利用率及工业炸药产品的出入库效率,较好的解决了工业炸药仓储过程中存在的优化问题。Aiming at the optimization problem of industrial explosives storage,the actual difficulties and requirements of industrial explosives storage management were analyzed in the paper,the industrial explosives storage scheme was proposed and the mathematical optimization model was established.According to the genetic algorithm to solve the problems in the storage model,a hybrid genetic algorithm based on information entropy and improved adaptive mutation operator was proposed to solve the model proposed.The experimental simulation results show that the solution of the model proposed by the algorithm has achieved good results in convergence accuracy and speed;At the same time,it improves the space utilization rate of industrial explosive warehouse groups and the efficiency of industrial explosive products storage and exit;It effectively solves the optimization problems in the storage process of industrial explosives.

关 键 词：工业炸药 仓储优化 信息熵 自适应变异 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]