Scheduling Optimization on Takeout Delivery Based on Hybrid Meta-heuristic Algorithm

被引：2

作者：

Sheng, Wen ^{[1
]}

Shao, Qianqian ^{[1
]}

Tong, Hengxing ^{[1
]}

Peng, Jianfeng ^{[1
]}

机构：

[1] Shenyang Jianzhu Univ, Transportat Engn Sch, Shenyang, Peoples R China

来源：

2021 13TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2021年

关键词：

takeout delivery; delivery scheduling optimization; ACO; GA; hybrid meta-heuristic algorithm; VEHICLE-ROUTING PROBLEM;

D O I：

10.1109/ICACI52617.2021.9435873

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

As a novel catering mode, the optimization of takeout delivery scheduling plays an important role in improving efficiency of delivery and the service level of catering enterprises. For the current takeout delivery patterns in China, a delivery scheduling optimization model was proposed with the purpose of minimizing the delivery distance. Moreover, a hybrid meta-heuristic algorithm was developed, with considering the strong robustness of ant colony algorithm (ACO) and excellent convergence ability of genetic algorithm (GA). Results of a series of experiments of a restaurant in Hunnan New District, Shenyang City demonstrate the efficiency of proposed model and the hybrid meta-heuristic algorithm.

引用

页码：372 / 377

页数：6

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