Research on Optimization of in-warehouse picking Model based on genetic algorithm
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Huang Wanjie, Wang Haotian, Xue Yibo
This paper mainly aims at the large amount of picking work and activity cost in the e-commerce distribution center, so optimizing the picking path and reducing the picking time is of great significance to improve the operation efficiency and reduce the cost of the distribution center. In this paper, according to the example route and way in which the picker enters the shelf, the picker is regarded as a particle and the classification path optimization strategy is adopted. it is composed of three kinds of distances, that is, between the goods grid, between the goods grid and the check table, and between the check table and the check table. Then the genetic algorithm based on Jenetics algorithm library is introduced to solve the problem, and the global optimal grid access and the walking path of the returned check station are iterated, and the shortest completion time of the solution is obtained. Then, aiming at the path planning problem of multi-starting point, multi-check station, multi-task single or even multi-picker, it is a multi-objective complex problem, which is properly reduced and optimized layer by layer. And reconsider the time impact of the order of tasks, each layer to find the optimal solution, then the final result must be optimal.
Optimized genetic algorithm; TSP problem; Multi-objective optimization problem; Pick goods in the warehouse