Improved Genetic Algorithm Research for Route Optimization of Logistic Distribution

The perfomance of neighborhood searching of GA with general mutation operator is not satisfiable. In the paper, an improved mutation operator is presented. After using GA with an improved mutation operator, the model of optimization of delivery route with single distribution center and simglevehicle is established. Standard test data are used for simulation. The proportional selection operator, tournament selection operator and truncation selection operator in GA are compared, and the result is that by using truncation selection operator, a better optimal effect can be obtained. A dynamic switching mutation operator is also proposed. It is based on 3-opt mutation operator, sub-router exchange mutation operator and two point exchange mutation operator. Simulation results show that the dynamic switching mutation operator can enhance the ability of the neighborhood searching, and GA using dynamic switching mutation operator can get a relatively stable result.