Logistics path planning method and device and driver scheduling method and device

Abstract

The invention discloses a logistics path planning method. The method comprises the steps of setting realistic constraint conditions of a target logistics path; obtaining initial planning path information of target logistics by adopting a saving algorithm; obtaining an optimal solution of the initial planning path by adopting a genetic algorithm; and planning a logistics path according to the optimal solution of the logistics path. The invention also discloses a driver scheduling method. By applying the logistics path planning method, the driver scheduling method comprises the following steps of: obtaining preset driver constraint conditions and planning the driver scheduling according to the genetic algorithm by combining with the obtained optimal logistics path; and generating driver scheduling information. The invention also discloses a logistics path planning device and a driver scheduling device. Through the realistic constraint condition-considered logistics path planning method and driver scheduling method, the established model is more accurate and closer to the actual situation; the operability is stronger; and the transportation cost, the labor cost and the time cost, which are caused by model deviation, of enterprises are reduced.

Description

technical field [0001] The invention belongs to the technical field of logistics resource allocation, and in particular relates to a logistics path planning method and device, and a driver scheduling method and device. Background technique [0002] The development of the logistics and distribution industry is changing with each passing day. Most of the domestic logistics companies still use more mature planning algorithms abroad for logistics route planning. For example, linear programming, dynamic programming, etc., gradually cannot meet the needs of the problem, and cannot catch up with the current development speed of the industry. Moreover, most of the existing enterprises outsource or operate their own transportation business. In driver scheduling and scheduling, all vehicles and personnel are dispatched manually based on experience. [0003] In order to achieve a reasonable arrangement of logistics distribution routes, at present, the existing technology adopts linear...

AI Technical Summary

Problems solved by technology

[0002] The development of the logistics and distribution industry is changing with each passing day. Most of the domestic logistics companies still use more mature planning algorithms abroad for logistics route planning. For example, linear programming, dynamic programming, etc., gradually cannot meet the needs of the problem, and cannot catch up with the current development speed of the industry. Moreover, most of the existing enterprises outsource or operate their own transportation business. In driver scheduling and scheduling, all vehicles and personnel are dispatched manually based on experience

[0003] In order to achieve a reasonable arrangement of logistics distribution routes, at present, the existing technology adopts linear programming or dynamic programming methods, which can obtain all feasible solutions, but the amount of calculation is large, and it is suitable for small-scale routing problems. The behavior of some organisms (such as particle swarm algorithm, genetic algorithm, bacterial foraging optimization algorithm, etc.) or physical phenomena (such as simulated annealing algorithm), randomly generate initial solutions, and continuously search and change in the feasible region according to these simulated behavior mechanisms , until a feasible solution close to the optimal solution of the problem is found, this method cannot guarantee to obtain the optimal solution, and even sometimes cannot determine the degree of closeness of the obtained dissociated optimal solution, and the planning algorithm currently used is very Little consideration is given to the realistic constraints in the logistics process, making the planned path impossible to land, resulting in cost and time consumption

[0004] Driver scheduling refers to formulating a reasonable plan to solve the problem of driver scheduling and allocation. It is an important content for transportation companies to improve competitiveness and cost control. Generally, all business orders in enterprises are dispatched by vehicle dispatchers. Vehicle selection based on the usage situation and the quantity of goods. Manual selection of the number of logistics vehicles, transportation routes and driver scheduling based on experience is highly subjective, resulting in low scheduling efficiency, long transportation time, low utilization of vehicle resources, and unreasonable driver scheduling. Unfair, serious empty driving situation and other issues

[0005] For the above problems, the prior art does not propose a good solution

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