Passenger vehicle transport vehicle scheduling method and device based on order dynamic priority

Abstract

The invention provides a passenger vehicle transport vehicle scheduling method and device based on order dynamic priority. The method comprises the following steps: acquiring a transport vehicle data set and an order data set; calculating the emergency degree of each order based on the current time, the latest delivery time of each order, the order adding time and the transportation time required for directly transporting the order from the order pickup point to the corresponding order delivery point, calculating the priority of each order based on each emergency degree, and determining the order to be transported in the scheduling period based on each priority; a greedy algorithm is adopted to obtain a vehicle scheduling initial solution set at the scheduling moment; dividing the vehicle scheduling initial solution set into a plurality of class clusters by taking the vehicle current position of each vehicle as a clustering center; establishing a transportation profit function at the scheduling moment, taking the transportation profit function as a target function, and adopting a tabu search algorithm to optimize feasible solutions in each cluster; and gathering and recombining the feasible solutions subjected to tabu optimization in each cluster to obtain an optimal vehicle scheduling solution at the scheduling moment.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method and device for dispatching passenger vehicles based on dynamic priority of orders. Background technique [0002] In recent years, with the rapid growth of my country's automobile production and sales, the automobile logistics industry has also achieved rapid development. In 2020, the scale of China's passenger vehicle logistics market will exceed 1 trillion yuan, of which transportation costs account for more than 40%. At present, domestic passenger vehicle transportation is still mainly based on roads. The cost of transportation will greatly increase the profit of the enterprise. [0003] The open heterogeneous fleet dynamic pickup and delivery problem with time window and dynamic priority, multi-warehouse, aperiodic, and divisible requirements aiming at maximizing corporate profits within a cycle time is an NP-hard problem. , is a variant of the classic VRP problem...

AI Technical Summary

Problems solved by technology

In 2020, the scale of China's passenger vehicle logistics market will exceed 1 trillion yuan, of which transportation costs will account for more than 40%. At present, domestic passenger vehicle transportation is still mainly based on roads. Therefore, if the logistics of passenger vehicles is reduced Transportation costs will greatly increase the profits of the business

[0003] However, the open heterogeneous fleet dynamic pick-up and delivery problem with time window and dynamic priority, multi-warehouse, non-periodic, and splittable demand aimed at maximizing enterprise profit within a cycle time is an NP-hard problem , is a variant of the classic VRP problem with capacity constraints, which is rarely studied by scholars

Most of the existing research focuses on the dynamic path planning problem and the pick-and-delivery problem with time window constraints, and there are very few studies considering the dynamic priority; the current research on the dynamic path planning problem, whether it is single-objective or multi-objective optimization, Most of them focus on the optimization goals of transportation costs, vehicle waiting time and driving time, number of service vehicles, service delay time, customer satisfaction, vehicle utilization rate, etc., and seldom consider the maximization of operating profits of the enterprise, so it is impossible to improve the efficiency of enterprises. Transportation profit, and waste of passenger car resources

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