基于仿真的O2O即时配送系统调度策略比较

Wenzhe Jin, Weihua Wu, Jialin Shi, Ming Gao
{"title":"基于仿真的O2O即时配送系统调度策略比较","authors":"Wenzhe Jin, Weihua Wu, Jialin Shi, Ming Gao","doi":"10.1109/ISKE47853.2019.9170408","DOIUrl":null,"url":null,"abstract":"O2O instant delivery is a key success factor for internet-driven traditional business revolution such as 020 fast food delivery and fetch and carry services. With its rapid development, it has to face a variety of instant delivery scheduling problems. These have become a major bottleneck for the instant delivery platforms and it’s decision makers. The traditional method based on human experience has been no longer suitable for the current scenarios with large-scale orders and randomness. Therefore, we define the scheduling problem and scheduling strategies of instant orders delivery based on the real-world investigation, and verify the feasibility of order scheduling strategies by establishing an integrated simulation platform including traffic, orders, customers and merchants based on the DRL’s sumo simulation library and the comparison of the three scheduling strategies are used to select the optimal strategy. We simply designed these three scheduling strategies: (1) RD: The platform randomly assigns the order to the rider. (2) SP-D: The generated order is dispatched in real time to the rider closest to the order. (3) BPD: After all the orders generated in a fixed period of time are put together, all the orders are dispatched to several riders. It was found that the performance of BP-D was better in the comparison of SP-D and BP-D. And we found that when it comes to dealing with large-scale orders, the BP-D can most effectively dispatch passengers, maximizing the benefits of merchants, passengers and platforms.","PeriodicalId":399084,"journal":{"name":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simulation Based Scheduling Strategies Comparison of O2O Instant Delivery System\",\"authors\":\"Wenzhe Jin, Weihua Wu, Jialin Shi, Ming Gao\",\"doi\":\"10.1109/ISKE47853.2019.9170408\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"O2O instant delivery is a key success factor for internet-driven traditional business revolution such as 020 fast food delivery and fetch and carry services. With its rapid development, it has to face a variety of instant delivery scheduling problems. These have become a major bottleneck for the instant delivery platforms and it’s decision makers. The traditional method based on human experience has been no longer suitable for the current scenarios with large-scale orders and randomness. Therefore, we define the scheduling problem and scheduling strategies of instant orders delivery based on the real-world investigation, and verify the feasibility of order scheduling strategies by establishing an integrated simulation platform including traffic, orders, customers and merchants based on the DRL’s sumo simulation library and the comparison of the three scheduling strategies are used to select the optimal strategy. We simply designed these three scheduling strategies: (1) RD: The platform randomly assigns the order to the rider. (2) SP-D: The generated order is dispatched in real time to the rider closest to the order. (3) BPD: After all the orders generated in a fixed period of time are put together, all the orders are dispatched to several riders. It was found that the performance of BP-D was better in the comparison of SP-D and BP-D. And we found that when it comes to dealing with large-scale orders, the BP-D can most effectively dispatch passengers, maximizing the benefits of merchants, passengers and platforms.\",\"PeriodicalId\":399084,\"journal\":{\"name\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISKE47853.2019.9170408\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 14th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISKE47853.2019.9170408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

O2O即时配送是互联网驱动的传统商业革命的关键成功因素,如020快餐外卖和取走服务。随着它的快速发展,它面临着各种各样的即时配送调度问题。这些已经成为即时交付平台及其决策者的主要瓶颈。传统的基于人类经验的方法已经不适合当前具有大阶次和随机性的场景。因此,我们在实际调研的基础上定义了即时订单交付的调度问题和调度策略,并基于DRL的相扑仿真库建立了包含流量、订单、客户和商家的综合仿真平台,验证了订单调度策略的可行性,并通过对比三种调度策略来选择最优策略。我们简单地设计了三种调度策略:(1)RD:平台随机给骑手分配顺序。(2) SP-D:生成的订单实时发送给离订单最近的骑手。(3) BPD:将固定时间内产生的所有订单放在一起后,将所有订单分配给几个骑手。对比SP-D和BP-D,发现BP-D的性能更好。我们发现,在处理大规模订单时,BP-D可以最有效地调度乘客,使商家、乘客和平台的利益最大化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Simulation Based Scheduling Strategies Comparison of O2O Instant Delivery System
O2O instant delivery is a key success factor for internet-driven traditional business revolution such as 020 fast food delivery and fetch and carry services. With its rapid development, it has to face a variety of instant delivery scheduling problems. These have become a major bottleneck for the instant delivery platforms and it’s decision makers. The traditional method based on human experience has been no longer suitable for the current scenarios with large-scale orders and randomness. Therefore, we define the scheduling problem and scheduling strategies of instant orders delivery based on the real-world investigation, and verify the feasibility of order scheduling strategies by establishing an integrated simulation platform including traffic, orders, customers and merchants based on the DRL’s sumo simulation library and the comparison of the three scheduling strategies are used to select the optimal strategy. We simply designed these three scheduling strategies: (1) RD: The platform randomly assigns the order to the rider. (2) SP-D: The generated order is dispatched in real time to the rider closest to the order. (3) BPD: After all the orders generated in a fixed period of time are put together, all the orders are dispatched to several riders. It was found that the performance of BP-D was better in the comparison of SP-D and BP-D. And we found that when it comes to dealing with large-scale orders, the BP-D can most effectively dispatch passengers, maximizing the benefits of merchants, passengers and platforms.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Incremental Learning for Transductive SVMs ISKE 2019 Table of Contents Consensus: The Minimum Cost Model based Robust Optimization A Learned Clause Deletion Strategy Based on Distance Ratio Effects of Real Estate Regulation Policy of Beijing Based on Discrete Dependent Variables Model
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1