X-Tobacco Cigarette Distribution Center Location Optimization Of Sorting System

This paper takes X-tobacco cigarette distribution center’s automatic sorting system as the research object, it studies the cigarette distribution optimization problem of automatic sorting system. This paper systematically reviews automatic sorting system optimization and the classical modeling method and solving method of the location optimization model. Based on the analysis, this paper constructs the cigarette automatic sorting system location optimization model of the X-tobacco cigarette distribution center according to the method from simple to complex. The main work of this paper are as follows,1This paper constructs the cigarette location optimization model of single order and multiple orders based on the single horizontal sorting device. Model takes the total time of all cigarettes in a conveyor belt as the objective function. On the basis of meeting the relevant assumptions and constraints, model considers the transmission time of the cigarettes in a conveyor and the interval time between adjacent orders when it has many orders. Through constructing the cigarette location optimization model of a single horizontal sorting device, sorting cost of the entire automatic sorting system reduces.2This paper constructs the cigarette location optimization model of single order and multiple orders based on two horizontal sorting devices. Model takes the total time of all cigarettes in a conveyor belt as the objective function. On the basis of meeting the relevant assumptions and constraints, model considers the transmission time of the cigarettes in a conveyor, the interval time between adjacent orders when it has many orders and waiting time of cigarettes when the same order in the different partitions needs meet. Through constructing the cigarette location optimization model of two horizontal sorting devices, sorting cost of the entire automatic sorting system reduces.3This paper uses numerical examples for simulation solution, analyzing the solving results and the sensitivity. At the same time, it analyzes each part of the time in the model. We can know the related effect of part time on the target function, which further verifies the correctness and rationality of the solving results.