Order optimization allocation method based on reliability evaluation of riders on intelligent food delivery platform

CN118674244BActive Publication Date: 2024-12-10DALIAN MARITIME UNIVERSITY
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Patent Information

Application Number
CN202411164420.3
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-08-23
Publication Date
2024-12-10
Estimated Expiration
2044-08-23

AI Technical Summary

Technical Problem

The traditional manual distribution method is difficult to ensure efficient and accurate distribution of takeaway orders, especially when riders have uneven reliability and complex delivery environments, it is impossible to effectively optimize the distribution of orders.

Method used

Based on the rider reliability evaluation of the intelligent takeaway platform, a multi-target takeaway order optimization distribution model is constructed, combined with linear weighted sum method and adaptive large neighborhood search algorithm, and the order optimization distribution strategy is constructed through simulated annealing mechanism to achieve the best of riders and orders. match.

Benefits of technology

提高了订单分配的效率和用户体验,减少了配送时间和成本,确保了订单的高效执行和准时送达,提升了用户满意度和平台竞争力。

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Abstract

The present invention discloses an order optimization allocation method based on the reliability evaluation of riders on an intelligent food delivery platform, including: S1: constructing a multi-objective food delivery order optimization allocation model with the goals of minimizing the total delivery cost of the food delivery platform, maximizing the rider reliability, and maximizing the customer satisfaction; S2: based on the linear weighted sum method, integrating the multi-objective food delivery order optimization allocation model to obtain a single objective function model; S3: constructing an order optimization allocation strategy based on an adaptive large neighborhood search algorithm combined with a simulated annealing mechanism; and obtaining an order optimization allocation scheme that optimizes the single objective function model based on the order optimization allocation strategy. The present invention solves the problem that the traditional manual allocation method is not only inefficient, but also difficult to ensure the optimality of order allocation, especially in the face of uneven rider reliability and complex and changeable delivery environment, and cannot effectively optimize order allocation.
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Citation Information

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