Vehicle path optimization method for multi-warehouse transportation

Abstract

The invention discloses a vehicle path optimization method for multi-warehouse transportation; the method comprises the steps: calculating the distance between a client node and all warehouses, distributing the client node to the nearest warehouse, and finding a part of optimal solutions for each warehouse and the client node distributed to the warehouse through employing an artificial bee colony algorithm after the distribution is completed; and combining the vehicle scheduling route sets aiming at the single warehouse node into one set to form a total vehicle scheduling route set aiming at the multi-warehouse vehicle route problem, thereby realizing optimization of the vehicle route. According to the method, the multi-warehouse backgrounds are classified into the single-warehouse backgrounds by setting the distribution, correction and combination stages, so that the vehicle path scheduling routes for each single warehouse can be calculated in parallel, the search range of the scheduling routes is narrowed, and the calculation efficiency is improved; in addition, due to the existence of following bees and itinerant bees in the bee colony, premature convergence caused by local optimum is not prone to occurring, and a better approximate solution can be found more easily.

Description

technical field [0001] The invention relates to the field of computer and information technology, in particular to a vehicle route optimization method for multi-warehouse transportation. Background technique [0002] Intelligent manufacturing supply chain is a new type of supply chain proposed under the influence of intelligent manufacturing and Industry 4.0 in recent years. It is powered by big data and works with the support of smart devices and smart algorithms. In the construction process of the intelligent manufacturing supply chain, resource scheduling is one of the core issues throughout the construction of the entire intelligent manufacturing supply chain. Vehicle resources, as an important part of the logistics system in the supply chain system, are of great value to suppliers. The vehicle scheduling problem is to formulate and optimize the scheduling strategy of the transport vehicles, and finally achieve the minimum total cost or other optimization goals under t...

AI Technical Summary

Problems solved by technology

[0007] The first algorithm is relatively short-sighted, because it can only achieve optimization at each step rather than global optimization, so it can only get a poor optimal solution

[0008] The second algorithm has two main disadvantages

The first is the low efficiency, which often requires a large number of groups and a large number of iterations

Secondly, it is easy to converge prematurely. Since the new generation of individuals is always roughly based on the previous generation of individuals, it is easy for the algorithm to fall into a local optimal solution and converge prematurely.

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