The Application of Modified Genetic Algorithm in Logistics Distribution Routing Optimization

摘要

Logistics distribution routing optimization is a problem of multiple objective and multiple constraints. Specific to two disadvantages of genetic algorithm, namely, the poor convergence rate and tendency of local optimum, this paper manages to propose a new adaptive immune genetic algorithm (AIGA), which makes use of a new vaccine selection strategy and vaccine operation approach and realizes the optimization of multiple target logistics distribution with the combination of parallel selection. The simulation result shows that both the convergence and efficiency are evidently improved, indicating that AIGA is a preferably better way to solve the problem of routing optimization.