A cost-optimized in-plant logistics distribution method

Abstract

A cost-optimized in-plant logistics distribution method claimed in the present invention proposes to adopt the principle of minimum order splitting, consider the time window and vehicle load constraints, and construct a mathematical model with the goal of minimizing the total distribution cost. The two-stage genetic algorithm is designed above, and the P logistics enterprise is used as an example for application research. MATLAB programming is used to solve the distribution scheme based on the principle of minimum order splitting, and it is compared with the distribution scheme based on the principle of shortest distance order splitting. The distribution plan based on the principle of order splitting is more optimal, which can effectively reduce the number of vehicles used, the number of pickups, the number of deliveries, and the number of pickups, improve the timeliness of delivery, and achieve the goal of reducing the total cost of delivery. At the same time, according to the distribution path and scene information of the order, the payment channel that best suits the order needs is obtained, so as to ensure the fast operation of the order life cycle.

Description

technical field [0001] The invention belongs to the technical field of logistics, and in particular relates to a cost-optimized in-plant logistics distribution method. Background technique [0002] With the improvement of people's living standards, the increasingly diversified needs of customers, and the rapid development of e-commerce, customers are more and more inclined to shop online, and the number of orders has greatly increased. Online orders have occupied most of the market share of omni-channel orders. In addition, the warehouse distribution is irregular, the types of goods stored are relatively single, and the number of single products is small, and a single warehouse is often unable to meet customer orders with many categories or a large number of orders (“multiple products in one order” or “multiple products in one order”). The realistic scenario of demand requires multiple distribution centers to meet, resulting in multi-warehouse distribution. When a customer b...

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 method of splitting orders gives priority to the shortest distance factor, which is likely to increase the number of vehicles used, duplicate delivery routes, and poor delivery timeliness. , resulting in increased distribution costs and poor customer service experience. Therefore, how to effectively split orders, conduct research on order processing methods, and choose reasonable order split principles, so as to effectively reduce the number of pick-ups, delivery times, and customer pick-ups The number of times is the key issue studied in this paper, and on this basis, follow-up distribution route planning is carried out to reduce the distribution cost of logistics enterprises and improve customer service experience

At the same time, for online payment methods, the general online payment method only relies on the payment order actively selected by the user, and cannot make a reasonable choice based on objective scene information. The user's subjective payment order may not reflect the objective demand. Therefore, there is an urgent need for an objective judgment method for the choice of payment method

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