{"title":"基于列行生成的继电器按需配送系统精确算法","authors":"Xueting He, Lu Zhen","doi":"10.1016/j.trb.2025.103223","DOIUrl":null,"url":null,"abstract":"<div><div>This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport it to another station and then another courier will transport it to its final destination. Using mixed-integer linear programing, this paper formulates a novel arc-based set-packing model with two types of columns, i.e., drone plans and courier plans, to maximize the profit from transporting a batch of orders. By combining branch-and-price, column-and-row generation, and some tailored acceleration tactics, an exact algorithm is designed and implemented to efficiently solve the model. Experimental results validate the efficiency of the proposed exact algorithm. Moreover, we find that large numbers of couriers, drones, or stations do not always substantially improve the system’s performance; if order due times are urgent, the benefit of drones (couriers) is more (less) significant. The model’s robustness and the applicability of our methodology in large-scale applications are validated.</div></div>","PeriodicalId":54418,"journal":{"name":"Transportation Research Part B-Methodological","volume":"196 ","pages":"Article 103223"},"PeriodicalIF":5.8000,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Column-and-row generation based exact algorithm for relay-based on-demand delivery systems\",\"authors\":\"Xueting He, Lu Zhen\",\"doi\":\"10.1016/j.trb.2025.103223\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport it to another station and then another courier will transport it to its final destination. Using mixed-integer linear programing, this paper formulates a novel arc-based set-packing model with two types of columns, i.e., drone plans and courier plans, to maximize the profit from transporting a batch of orders. By combining branch-and-price, column-and-row generation, and some tailored acceleration tactics, an exact algorithm is designed and implemented to efficiently solve the model. Experimental results validate the efficiency of the proposed exact algorithm. Moreover, we find that large numbers of couriers, drones, or stations do not always substantially improve the system’s performance; if order due times are urgent, the benefit of drones (couriers) is more (less) significant. The model’s robustness and the applicability of our methodology in large-scale applications are validated.</div></div>\",\"PeriodicalId\":54418,\"journal\":{\"name\":\"Transportation Research Part B-Methodological\",\"volume\":\"196 \",\"pages\":\"Article 103223\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2025-04-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part B-Methodological\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0191261525000724\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part B-Methodological","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0191261525000724","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Column-and-row generation based exact algorithm for relay-based on-demand delivery systems
This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport it to another station and then another courier will transport it to its final destination. Using mixed-integer linear programing, this paper formulates a novel arc-based set-packing model with two types of columns, i.e., drone plans and courier plans, to maximize the profit from transporting a batch of orders. By combining branch-and-price, column-and-row generation, and some tailored acceleration tactics, an exact algorithm is designed and implemented to efficiently solve the model. Experimental results validate the efficiency of the proposed exact algorithm. Moreover, we find that large numbers of couriers, drones, or stations do not always substantially improve the system’s performance; if order due times are urgent, the benefit of drones (couriers) is more (less) significant. The model’s robustness and the applicability of our methodology in large-scale applications are validated.
期刊介绍:
Transportation Research: Part B publishes papers on all methodological aspects of the subject, particularly those that require mathematical analysis. The general theme of the journal is the development and solution of problems that are adequately motivated to deal with important aspects of the design and/or analysis of transportation systems. Areas covered include: traffic flow; design and analysis of transportation networks; control and scheduling; optimization; queuing theory; logistics; supply chains; development and application of statistical, econometric and mathematical models to address transportation problems; cost models; pricing and/or investment; traveler or shipper behavior; cost-benefit methodologies.