An online order distribution and delivery method based on a scoring mechanism and route planning

Abstract

The invention provides an online order distribution and delivery method based on a scoring mechanism and path planning. The method comprises the following steps: firstly, orders in a certain time range of the same region are merged through a clustering algorithm; then, the historical distribution information of the rider is obtained by mining the historical distribution data of the rider in the order platform, and whether the rider matches the sub-orders in the order set is calculated; then the scores of the riders are calculated in the set of matched riders; the distribution information is preferentially pushed to the matched first rider with the highest score, and if the rider gives up, the distribution information is pushed to the matched second rider with the second highest score, andforwarded three times in the same way, and if no one takes orders, the distribution information is distributed to the snatching pool for the matched rider to snatch orders; finally, the route distribution scheme of the received single rider is determined by the cultural genetic algorithm. According to the order distribution and distribution method of the invention, the order distribution balance can be maintained while the customer experience is guaranteed, the distribution cost is further reduced, and the distribution efficiency is improved.

Description

technical field [0001] The invention relates to the technical fields of data mining, intelligent optimization, and intelligent logistics distribution, and in particular to an online order distribution and delivery method based on scoring mechanism and path planning. Background technique [0002] The current takeaway orders are generally served according to the order of the order time, and then the order task is posted to the delivery platform to wait for the rider to grab the order. After the rider grabs the order, he first goes to the merchant to pick up the food, and then delivers the order to the customer. It often happens that some riders blindly grab orders, resulting in resources being too concentrated in a small number of riders while the rest of the riders are idle and waiting. Due to the heavy delivery tasks of these riders, the delivery time is often too long, and customers cannot get the goods on time. Moreover, riders usually only deliver customers' orders based...

AI Technical Summary

Problems solved by technology

This method meets the customer's requirements for delivery time, but does not fully consider the optimization of transportation distance, task allocation, etc.

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