Supply Chain Schedule Management with Genetic Algorithm

In a modern logistics system, it is a very important issue how to organize transportation and "distribution" in a reasonable way in order to reduce the cost of "storage". Transportation is the most crucial part of the modern logistics subsystem. Transport plays an important role in the development of our country, for example by expanding the scope of distribution, expanding the tangibility of markets and promoting the division of labour in society. The aim of this work is to study the modelling of supply chain logistics and transport scheduling based on an improved genetic algorithm. Based on the study of this method, it is improved and compared with the control parameters of the genetic algorithm. Next, the supply chain logistics and transportation scheduling problem studied in this paper is described, the assumptions and definitions of the supply chain scheduling model are explained, the process of constructing the supply chain model is analysed and it is solved using the improved genetic algorithm. Experimental results show that this algorithm is able to bypass the shortcomings of traditional genetic algorithms and thus obtain satisfactory global optima.