Cargo stowage calculation method based on cargo distribution site, cargo volume and vehicle type

Abstract

The invention discloses a cargo stowage calculation method based on cargo distribution site, cargo volume and vehicle type, which is characterized by comprising the following steps of: S1, inputting all available vehicle information including vehicle types, vehicle quantity upper limits corresponding to the vehicle types, and loading spaces of the vehicle types; S2, screening out the vehicle typecapacity with the size or weight larger than the maximum vehicle type capacity, and removing the vehicle type capacity from the intelligent combination list for manual processing; S3, ranking the vehicle types in a descending order according to the vehicle type ranking volume, and outputting a vehicle type ranking sequence L (L = {1, 2, 3... t}) and the corresponding vehicle upper limit number K1(l = 1, 2, 3... t); and S4, inputting distribution area information A (A = {1, 2, 3... m}) and all non-combined DO order information D (D = {1, 2, 3... n}), wherein the DO order information comprisesthe volume Vd, the weight qd and the destination da. By means of positioning information of goods and navigation software, attributes of various goods, vehicle load and the like, the stowage rate andthe average kilometer benefit of the single vehicle are improved by analyzing early-stage configuration data and depending on a reasonable stowage algorithm.

Description

technical field [0001] The invention relates to the technical field of intelligent stowage algorithms for less-than-truckload collection, in particular to a cargo stowage calculation method based on cargo distribution points, cargo volumes, and vehicle models. Background technique [0002] With the continuous increase of freight volume, various logistics companies and warehousing and distribution companies began to expand their transportation capacity, which led to an increase in their own operating costs. How to accurately expand, allocate transportation capacity, and maximize the profit of each vehicle has become the need of various logistics and distribution companies. The problem to be solved is that the distribution method of the existing logistics park is based on the volume of the total waybill, roughly estimating the type and quantity of vehicles used, and then loading the goods. This approach ensures the delivery rate of the goods, but due to the lack of accurate ca...

AI Technical Summary

Problems solved by technology

[0002] With the continuous increase of freight volume, various logistics companies and warehousing and distribution companies began to expand their transportation capacity, which led to an increase in their own operating costs. How to accurately expand, allocate transportation capacity, and maximize the profit of each vehicle has become the need of various logistics and distribution companies. The problem to be solved is that the distribution method of the existing logistics park is based on the volume of the total waybill, roughly estimating the type and quantity of vehicles used, a

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