Shengdong Li , Dajie Zuo , Wenqing Li , Yongxiang Zhang , Li Shi
{"title":"大规模高速铁路网的货运列车线路规划:基于整数本德斯分解的分支与切割算法","authors":"Shengdong Li , Dajie Zuo , Wenqing Li , Yongxiang Zhang , Li Shi","doi":"10.1016/j.tre.2024.103750","DOIUrl":null,"url":null,"abstract":"<div><p>This paper aims to study and address the problem of completely re-scheduling high-speed freight train line plans under the conditions of a large-scale network, particularly for direct freight trains between central network nodes. First, we constructed a line pool of candidate trains. Then, considering constraints such as flow balance, station capacity, and train transport capacity, we formulated an integer programming model with 0–1 variables. The objective is to minimize train operation costs and freight transfer fees, determining the origin and destination stations and the operating frequency of freight trains. To address the structural characteristics of the model, an integer Benders decomposition-based branch-and-cut algorithm (IBD-BCA) is proposed. This algorithm, within the framework of branch-and-bound, solves the master problem decomposed by Benders and adds two sets of integer Benders cuts to achieve the optimal solution of the model. To demonstrate the effectiveness and performance of the model and algorithm, numerical experiments were conducted based on actual data from the main high-speed railway network in China. The results show that the IBD-BCA in this study can obtain optimal solutions within a reasonable time and requires adding a relatively small number of cuts during the search process. Compared with branch-and-bound algorithms and direct solving using Gurobi, the IBD-BCA proposed maintains sufficient efficiency when dealing with large-scale problems. Additionally, sensitivity analyses of parameters such as capacity and costs validate the robustness and scalability of the presented model and algorithm.</p></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Freight train line planning for large-scale high-speed rail network: An integer Benders decomposition-based branch-and-cut algorithm\",\"authors\":\"Shengdong Li , Dajie Zuo , Wenqing Li , Yongxiang Zhang , Li Shi\",\"doi\":\"10.1016/j.tre.2024.103750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper aims to study and address the problem of completely re-scheduling high-speed freight train line plans under the conditions of a large-scale network, particularly for direct freight trains between central network nodes. First, we constructed a line pool of candidate trains. Then, considering constraints such as flow balance, station capacity, and train transport capacity, we formulated an integer programming model with 0–1 variables. The objective is to minimize train operation costs and freight transfer fees, determining the origin and destination stations and the operating frequency of freight trains. To address the structural characteristics of the model, an integer Benders decomposition-based branch-and-cut algorithm (IBD-BCA) is proposed. This algorithm, within the framework of branch-and-bound, solves the master problem decomposed by Benders and adds two sets of integer Benders cuts to achieve the optimal solution of the model. To demonstrate the effectiveness and performance of the model and algorithm, numerical experiments were conducted based on actual data from the main high-speed railway network in China. The results show that the IBD-BCA in this study can obtain optimal solutions within a reasonable time and requires adding a relatively small number of cuts during the search process. Compared with branch-and-bound algorithms and direct solving using Gurobi, the IBD-BCA proposed maintains sufficient efficiency when dealing with large-scale problems. Additionally, sensitivity analyses of parameters such as capacity and costs validate the robustness and scalability of the presented model and algorithm.</p></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554524003417\",\"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 E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554524003417","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Freight train line planning for large-scale high-speed rail network: An integer Benders decomposition-based branch-and-cut algorithm
This paper aims to study and address the problem of completely re-scheduling high-speed freight train line plans under the conditions of a large-scale network, particularly for direct freight trains between central network nodes. First, we constructed a line pool of candidate trains. Then, considering constraints such as flow balance, station capacity, and train transport capacity, we formulated an integer programming model with 0–1 variables. The objective is to minimize train operation costs and freight transfer fees, determining the origin and destination stations and the operating frequency of freight trains. To address the structural characteristics of the model, an integer Benders decomposition-based branch-and-cut algorithm (IBD-BCA) is proposed. This algorithm, within the framework of branch-and-bound, solves the master problem decomposed by Benders and adds two sets of integer Benders cuts to achieve the optimal solution of the model. To demonstrate the effectiveness and performance of the model and algorithm, numerical experiments were conducted based on actual data from the main high-speed railway network in China. The results show that the IBD-BCA in this study can obtain optimal solutions within a reasonable time and requires adding a relatively small number of cuts during the search process. Compared with branch-and-bound algorithms and direct solving using Gurobi, the IBD-BCA proposed maintains sufficient efficiency when dealing with large-scale problems. Additionally, sensitivity analyses of parameters such as capacity and costs validate the robustness and scalability of the presented model and algorithm.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.