Abstract
With the rapid development of e-commerce and the global economy, order picking mode of multiple batches and small quantities becoming more and more, which makes artificial picking system occupy a larger proportion in a variety of ways. The optimization study of the artificial person picking system has a crucial role to enhance the efficiency of batch picking, then increasing customer satisfaction. In this paper, according to the characteristics of the problem, Genetic algorithm was selected as the model's algorithm. The detailed design of coding, crossover method, genetic algorithm in solving process variation method, is used to realize the optimization of the model.
Highlights
The order batching problem expressed in mathematical language is the order needs to be chosen by the right way to carry on the batch, And through the calculate and determine the picking order so that to solve the objective function to achieve the optimal
This chapter based on the shortest distance as the objective function of the order batching model. and Design genetic algorithm of order batching problem
The reason that the application of genetic algorithm is a batch order has been proved to be NP problem, through accurate calculation method is difficult to obtain the optimal solution of the problem, And the common optimization algorithm has limitations in the optimization of efficiency, it is difficult to be accepted within the scope of the time to find the optimal solutions to the problem, it is necessary through an intelligent algorithm to solve the target[3]
Summary
The order batching problem expressed in mathematical language is the order needs to be chosen by the right way to carry on the batch, And through the calculate and determine the picking order so that to solve the objective function to achieve the optimal. The model has two objectives[1,2]: to reduce the walking distance in the selection process or walking time. This chapter based on the shortest distance as the objective function of the order batching model. Design genetic algorithm of order batching problem. The reason that the application of genetic algorithm is a batch order has been proved to be NP problem, through accurate calculation method is difficult to obtain the optimal solution of the problem, And the common optimization algorithm has limitations in the optimization of efficiency, it is difficult to be accepted within the scope of the time to find the optimal solutions to the problem, it is necessary through an intelligent algorithm to solve the target[3]. There are 3 Levels titles in an article to make ideas clear: (1)Order picking model preparation (2)Order picking model establishment (3)Design of the Genetic Algorithms
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