Vehicle logistics scheduling method and device, storage medium, and terminal based on ant colony algorithm

A scheduling method and ant colony algorithm technology are applied to storage media, terminals, and the field of vehicle logistics scheduling methods and devices based on ant colony algorithm, which can solve the problem of less consideration of variables, low utilization rate of transportation resources, and slow order response speed. and other problems to achieve the effect of improving real-time performance

Active Publication Date: 2020-10-16
ANJI AUTOMOTIVE LOGISTICS +1
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Problems solved by technology

Such a vehicle logistics scheduling method has many disadvantages, such as few variables to consider, non-optimal scheduling plan, low utilization rate of transportation resources, and slow order response speed, which cannot meet the expectations of automakers and customers.

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  • Vehicle logistics scheduling method and device, storage medium, and terminal based on ant colony algorithm
  • Vehicle logistics scheduling method and device, storage medium, and terminal based on ant colony algorithm
  • Vehicle logistics scheduling method and device, storage medium, and terminal based on ant colony algorithm

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Embodiment Construction

[0040] Those skilled in the art understand that, as mentioned in the background technology, the traditional vehicle logistics scheduling mode does not optimize the loading of task objectives, nor does it fully consider the constraint requirements of the input orders themselves, but simply assigns orders to vehicles manually The way to form a scheduling plan (that is, scheduling scheme). It is precisely because of the deficiencies in manual scheduling in the existing vehicle logistics scheduling scheme that there are many shortcomings such as few variables to consider, non-optimal scheduling scheme, low utilization rate of transportation resources, and full order response speed, which cannot be used in practical applications. Satisfying the constraints proposed from the perspective of business contracts and other aspects will cause damage to stakeholders in all aspects of the task, and will result in invalid solutions due to ignorance of some realistic factors in the scheduling ...

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Abstract

The invention relates to a vehicle logistics scheduling method and a device based on ant colony algorithm, a storage medium and a terminal. The method comprises the following steps: acquiring vehiclelogistics data, wherein the vehicle logistics data comprises order data and transportation capacity data; Acquiring M candidate allocation schemes based on the vehicle logistics data, wherein, M >= 1;Recording the candidate allocation scheme as an ant, recording a set of M ants as an ant colony, selecting ants with the largest target vector from the ant colony during the transfer period of each ant colony, and recording a projection of the ants on a preset target set as a target vector corresponding to the ant; When the transfer state of the ant colony satisfies the preset termination condition, determining the allocation scheme corresponding to the ant with the largest target vector selected during the last transfer as the optimal scheduling scheme. The scheme provided by the invention can realize the automatic dispatching of the whole vehicle logistics, is conducive to realizing the optimal dispatching, and reduces the dynamic dispatching cost of the freight car as a whole.

Description

technical field [0001] The present invention relates to the technical field of automobile logistics, in particular to a vehicle logistics scheduling method and device, storage medium, and terminal based on an ant colony algorithm. Background technique [0002] Complete vehicle logistics refers to a series of activities and processes in which complete vehicles are transported from OEMs, distribution sites, and dealers to end customers. Vehicle logistics scheduling needs to solve a series of problems such as logistics route planning, loading and vehicle scheduling. [0003] The factors involved in the existing vehicle logistics scheduling are relatively complex, with many constraints and multiple and mutually restrictive objectives, including OEMs and their warehouses, logistics companies and their transit warehouses, carriers and their contract drivers, dealers and their warehouses, etc. In many aspects, it is a multi-objective optimization problem in general. [0004] Howev...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06N3/00G06Q10/08
CPCG06N3/006G06Q10/0631G06Q10/083
Inventor 金忠孝梁亮
Owner ANJI AUTOMOTIVE LOGISTICS
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