基于遗传算法的冷链物流智能监测及预警

Intelligent monitoring and early warning of cold chain logistics based on genetic algorithm

针对水产品冷链物流运输过程中保鲜程度智能监测及预警问题,提出了一种基于改进遗传算法的水产品冷链物流保鲜程度智能监测及预警方法.该方法首先针对传统遗传算法自定义了交叉和变异的应用概率,增加了算法的收敛速度,将改进的算法应用于特定温度下的冷藏车中,推导时间与水产品腐败释放气体的函数关系,建立腐化方程,并在实际运输中,实时监测产生的气体与时间之间的函数关系,并在异常情况下进行报警.

Aiming at the problem of intelligent monitoring and early warning of the degree of freshness preservation in the cold chain logistics transportation of aquatic products,an intelligent monitoring and early warning method for the degree of freshness preservation of aquatic products in cold chain logistics based on an improved genetic algorithm is proposed.The method is first customized for the traditional genetic algorithm.The application probability of crossover and mutation has been increased,and the convergence speed of the algorithm has been increased.The improved algorithm is applied to refrigerated trucks at a specific temperature to derive the functional relationship between time and the gas released by aquatic product corruption,establish the corruption equation,and use it in actual transportation.Real-time monitoring of the functional relationship between the generated gas and time,and alarm in abnormal situations.