Research And Implementation Of Multi-point Multi-source Optimal Path Algorithm In Dynamic Logistics

Logistics distribution occupies a very important factor in the enterprise supply chain.Efficient logistics distribution can save enterprise costs and reduce delivery time.The key to achieving efficient logistics distribution is to optimize the path,therefore,this paper studies the multi-point multi-source optimal path algorithm in dynamic logistics based on the actual situation of logistics distribution.Multi-point multi-source refers to the delivery from multiple warehouses to multiple distant destinations.At present,there have been many research results in solving the problem of vehicle distribution route,but the problem of multi-point and multi-source has not been well solved,to this end,this paper fully considers the actual distribution scenario to establish a logistics distribution model,combined with the actual enterprise application,to achieve the best path distribution of multi-point and multi-source dynamic logistics.The specific research contents of this paper are as follows:(1)Optimize the shortest path algorithm between two points on the map,and reach all demand points in the fastest speed and the shortest time according to different customer requirements,while minimizing logistics costs.A linear weighted optimization model is established by giving the congestion coefficient,time threshold value and cost threshold value of each line in the urban road network.The dynamic Dijkstra algorithm is used to solve the optimal path under two different state requirements,namely,optimal path planning under time and cost equilibrium and dynamic emergency time constraints.(2)Aiming at the diversification of goods demand in the actual distribution process and the path optimization problem of multi-vehicle delivery and no-load rate,this paper proposes a new multi-point multi-source optimal path distribution method based on weight correction.This method realizes the sorting and delivery of goods from multiple warehouses according to various different goods requirements,and the cost is the smallest.The main research is the single vehicle distribution when the demand is greater than the vehicle's own weight.At this time,a comprehensive ratio analysis is needed on the distance and demand of the demand point,and the warehouse of the first distribution and the destination of the priority distribution are determined.After the correction of the capacity difference,the common delivery of multiple destinations is realized.(3)Establish a vehicle loading and distribution path model and optimize the solution for the newly proposed distribution plan.Constrained by multi-point multi-source,weight correction,optimal path,etc.,a new way of simulating cell division is used to generate the next generation.By improving the existing genetic algorithm to solve the problem,optimizing the generation of initial population,quickly obtaining the global optimal solution,jumping out of genetic premature convergence and finding the optimal path,the effectiveness of the algorithm is verified by experiments.Providing better service to customers with efficient distribution mode while reducing costs for enterprises.(4)Combined with the above research content,the best path algorithm between two points is applied to solve the multi-point multi-source optimal path problem,and the optimal driving route of logistics distribution is planned.And build a dynamic logistics system,which includes modules such as logistics and transportation scheduling and dynamic logistics information management,which can quickly respond to large-scale logistics and distribution of enterprises,save logistics costs and improve distribution efficiency.