In-plant logistics distribution method oriented to cost optimization

Abstract

According to the in-plant logistics distribution method for cost optimization, the minimum order splitting principle is adopted, time windows and vehicle loading quantity constraints are considered, a mathematical model with the minimum distribution total cost as the target is constructed, a two-stage genetic algorithm is designed on the basis of the genetic algorithm, application research is carried out with a P logistics enterprise as an example, and the optimal distribution cost is obtained. The distribution scheme based on the minimum order splitting principle is solved by applying MATLAB programming and compared with the distribution scheme based on the shortest distance order splitting principle, and the result shows that the distribution scheme based on the minimum order splitting principle is better, the number of used vehicles, the number of goods taking times, the number of distribution times and the number of goods taking times can be effectively reduced, the distribution timeliness is improved, and the distribution efficiency is improved. The purpose of reducing the total distribution cost is achieved. Meanwhile, the payment channel most suitable for the order demand is obtained according to the distribution path and scene information of the order, thereby guaranteeing the quick operation of the life cycle of the order.

Description

technical field [0001] The invention belongs to the technical field of logistics, and in particular relates to a cost-optimized in-factory logistics distribution method. Background technique [0002] With the improvement of people's living standards, the increasingly diverse needs of customers, and the rapid development of e-commerce, customers are more and more inclined to shop online, and the order volume has increased greatly. Online orders have occupied most of the market share of omni-channel orders. In addition, the distribution of goods in the warehouse is irregular, the types of goods stored are relatively single, and the number of single-item goods is small. A single warehouse often cannot satisfy customers with many orders or a large number of orders ("one order with multiple products" or "one order with multiple quantities") The reality of the demand requires multiple distribution centers to meet, resulting in multi-warehouse distribution. When a customer purchase...

AI Technical Summary

Problems solved by technology

[0002] With the improvement of people's living standards, the increasingly diverse needs of customers, and the rapid development of e-commerce, customers are more and more inclined to shop online, and the order volume has increased greatly. Online orders have occupied most of the market share of omni-channel orders. In addition, the distribution of goods in the warehouse is irregular, the types of goods stored are relatively single, and the number of single-item goods is small. A single warehouse often cannot satisfy customers with many orders or a large number of orders ("one order with multiple products" or "one order with multiple quantities") The reality of demand requires multiple distribution centers to meet, resulting in multi-warehouse distribution. When a customer purchases a product with multiple categories or a large number of single items, and it is stored in multiple warehouses, the order will be split. The problem

[0003] When most logistics companies face order splitting, the order processing method is often based on the principle of the shortest distance to split the order. This met

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