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Internet e-commerce storage dynamic scheduling method considering real-time orders

A dynamic scheduling and Internet technology, applied in the direction of instruments, calculation models, data processing applications, etc., can solve the problem of less dynamic customer orders involved, and achieve the effect of ensuring solution accuracy and convergence efficiency, improving diversity, and improving real-time performance

Pending Publication Date: 2021-05-07
HENAN INST OF SCI & TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] So far, the three-dimensional warehouse scheduling problems considered by scholars mainly focus on static order picking, and dynamic customer orders are less involved.

Method used

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  • Internet e-commerce storage dynamic scheduling method considering real-time orders
  • Internet e-commerce storage dynamic scheduling method considering real-time orders
  • Internet e-commerce storage dynamic scheduling method considering real-time orders

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Embodiment 1

[0050] see figure 1 , the present invention considers the e-commerce warehouse scheduling method of dynamic customer orders, and its specific steps are as follows:

[0051] (1) Establish goals and establish mathematical models

[0052] Usually, the warehouse scheduling system will generate a stacker picking task scheduling plan based on the customer order information known in advance. However, in the process of picking by the stacker according to the specified scheduling plan, new customer orders may be generated. Considering the dynamic and real-time nature of scheduling, it is necessary to update the original scheduling plan when the new customer order is generated. Adjust to meet new customer order real-time picking requirements. When a new customer order is generated, the stacker may be on the way to the warehouse where the order is located. At this time, it is not allowed to terminate the picking operation of the order, and a new scheduling plan can only be generated af...

Embodiment 2

[0090] In this embodiment, an e-commerce company considers the storage scheduling optimization problem of customers' dynamic orders, and uses the present invention to find the optimal solution or suboptimal solution that satisfies the constraint conditions. The overall layout of the e-commerce automated three-dimensional warehouse is as follows: image 3 shown.

[0091] (1) Problem overview

[0092]According to the above-mentioned technical scheme, an example of an e-commerce automated three-dimensional warehouse is given as an application background. At the same time, it is compared with the standard Grasshopper Algorithm (GOA) in the literature ([1] Saremi et al. Grasshopper optimization algorithm: theory and application. Advances in Engineering Software, 2017.), Improved Particle Swarm Optimization Algorithm (HCLPSO) ([2]Lynn et al.Heterogeneous comprehensive learning particle swarm optimization with enhanced exploration and exploitation.Swarm and Evolutionary Computation,...

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Abstract

The invention discloses an internet e-commerce storage dynamic scheduling method considering real-time orders, which takes intelligent storage as a starting point, introduces dynamic characteristics of customer random orders into a storage scheduling link, and establishes a storage dynamic scheduling optimization model with constraint conditions according to a to-be-optimized target. The grasshopper algorithm is adopted to solve the model, aiming at the defects that the grasshopper algorithm is low in convergence speed and prone to falling into local optimum, a multi-learning strategy is introduced to increase the probability that excellent genes are inherited to offspring, a heuristic migration mechanism based on population distribution characteristics is introduced to flexibly adjust the diversity of grasshopper populations, so that the local and global optimization capacity of the grasshopper algorithm is effectively improved. The e-commerce storage dynamic scheduling optimization problem is solved based on the improved grasshopper algorithm, the result shows that the optimization efficiency and quality of the improved grasshopper algorithm are obviously improved, the sorting efficiency of e-commerce storage is improved, and the sorting flexibility of e-commerce storage is improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent three-dimensional warehousing, and in particular relates to a dynamic scheduling method for Internet e-commerce warehousing considering real-time orders. Background technique [0002] The application of "Internet +" technology has further broadened the sales channels of products. Online transactions have become a new trend of consumption. With the spread of the new crown pneumonia epidemic around the world, online transactions are gradually replacing offline transactions, thus giving birth to online products. A large-scale e-commerce platform for model selection and ordering. For consumers, online transactions reduce the intermediate links such as wholesale and retail, so that they can buy high-quality and cheap commodities; for manufacturers, online transactions can reduce inventory or even achieve zero inventory, thus reducing The inventory cost of the enterprise. However, warehousing and ...

Claims

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Application Information

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IPC IPC(8): G06Q10/08G06N3/00
CPCG06Q10/087G06N3/006
Inventor 杨文强陈锡渠张素君杜留锋彭占磊孔晓红秦国庆
Owner HENAN INST OF SCI & TECH
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