O2O take-out platform intelligent scheduling and route optimization method

Abstract

The present invention discloses an O2O take-out platform intelligent scheduling and route optimization method. The method comprises the following steps: performing preprocessing of take-out orders; rapidly generating a take-out order intelligent assignment model; and determining a delivery route, and estimating a delivery cost. The O2O take-out platform intelligent scheduling and route optimization method considers factors such as delivery time and delay cost while preprocessing of the take-out order data so as to reduce the calculated quantity of the assignment and route selection links. The method improves the take-out order assignment efficiency for the intelligent and rapid assignment for the take-out orders. The method employs an idea that take-out delivery needs to firstly take delivery of goods from a merchant and then deliver goods to clients to rapidly select a delivery route. The method employs take-out order preprocessing to complete the initialization of parameters such as dynamic time, deliveryman position, capacity constraint and delivery and delay unit cost, a deliveryman is selected for an order to be assigned according to the distance between the order to be assigned and an assigned order, and the idea that take-out delivery needs to firstly take delivery of goods from a merchant and then deliver goods to clients is employed to rapidly select delivery routes for each deliveryman.

Description

technical field [0001] The invention belongs to logistics dispatching and optimization technology, in particular to an order intelligent dispatching and route optimization method of an O2O takeaway platform. Background technique [0002] There are currently many O2O food delivery platforms, such as Baidu Waimai, Ele.me, Meituan, etc., and food delivery scheduling and delivery are important supporting links of catering O2O, and their advantages and disadvantages directly affect the further expansion and development of Internet food delivery. However, due to many reasons such as regional restrictions, high timeliness requirements, and relatively low profit points, the logistics cost of food delivery delivery remains high, and delivery scheduling and delivery optimization are the biggest problems for food delivery platforms. [0003] At present, there are few public literatures dedicated to O2O food delivery platform food delivery scheduling and delivery routes, and most of the...

AI Technical Summary

Problems solved by technology

However, these methods are unsatisfactory when applied to order scheduling and delivery route selection on O2O food delivery platforms: 1) Because food delivery delivery generally divides reasonable areas and the distance is not too far away, and in order to avoid affecting the quality and taste of food, generally It is required to deliver the meal to the customer within 30 minutes, and there is a strict delivery time constraint; 2) The traditional logistics distribution optimization problem has a fixed distribution center (generally fewer centers) and a closed-loop structure in which vehicles depart from the center and finally return to the center. For the optimization of takeaway delivery routes, it is necessary to ensure that the merchants who ordered the orders first pick up the meals and then deliver them to the customers. The merchants and customers cannot be treated equally. The locations of the merchants and customers of the orders are dynamic requirements and the location of the delivery personnel is not fixed during scheduling; 3) The traditional logistics distribution optimization problem is transformed into the Traveling Salesman Problem (TSP) after scheduling. Finding the optimal route is an NP problem, and heuristic algorithms are often used to solve it. Assign a courier and give a recommended route

The joint influence of these factors makes the processing of O2O food delivery platform food delivery scheduling and delivery optimization more complicated.

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