RECIFE-SAT: A MILP-based algorithm for the railway saturation problem

被引:1
|
作者
Pellegrini P. [1 ]
Marlière G. [2 ]
Rodriguez J. [2 ]
机构
[1] Univ Lille Nord de France, F-59000 Lille, IFSTTAR, COSYS, LEOST, Villeneuve dAscq
[2] Univ Lille Nord de France, F-59000 Lille, IFSTTAR, COSYS, ESTAS, Villeneuve dAscq
来源
关键词
Microscopic representation; Mixed-integer linear programming; Railway capacity; Saturation problem;
D O I
10.1016/j.jrtpm.2017.08.001
中图分类号
学科分类号
摘要
Measuring capacity of railway infrastructures is a problem even in its definition. In this paper, we propose RECIFE-SAT, a MILP-based algorithm to quantify capacity by solving the saturation problem. This problem consists of saturating an infrastructure by adding as many trains as possible to an existing (possibly empty) timetable. Specifically, RECIFE-SAT considers a large set of potentially interesting saturation trains and integrates them in the timetable whenever possible. This integration is feasible only when it does not imply the emergence of any conflict with other trains. Thanks to a novel approach to microscopically represent the infrastructure, RECIFE-SAT guarantees the absence of conflicts based on the actual interlocking system deployed in reality. Hence, it can really quantify the actual capacity of the infrastructure considered. The presented version of RECIFE-SAT has two objective functions, namely it maximizes the number of saturation trains scheduled and the number of freight ones. In an experimental analysis performed in collaboration with the French infrastructure manager, we show the promising performance of RECIFE-SAT. To the best of our knowledge, RECIFE-SAT is the first algorithm which is shown to be capable of saturating rather large railway networks considering a microscopic infrastructure representation. © 2017 Elsevier Ltd
引用
收藏
页码:19 / 32
页数:13
相关论文
共 41 条
  • [21] A parallel algorithm for solving sat problem based on dna computing
    Darehmiraki, M.
    International Journal of Computers and Applications, 2009, 31 (02) : 128 - 131
  • [22] A SAT Based Effective Algorithm for the Directed Hamiltonian Cycle Problem
    Jaeger, Gerold
    Zhang, Weixiong
    COMPUTER SCIENCE - THEORY AND APPLICATIONS, 2010, 6072 : 216 - +
  • [23] Solving SAT Problem Based on Hybrid Differential Evolution Algorithm
    Liu, Kunqi
    Zhang, Jingmin
    Liu, Gang
    Kang, Lishan
    COMPUTATIONAL INTELLIGENCE AND INTELLIGENT SYSTEMS, 2009, 51 : 240 - +
  • [24] Hardware in the Loop Simulation of MILP Algorithm based Railway Traffic Re-scheduling during Disturbances
    Joelianto, Endra
    Setiawan, Aan
    Chaerani, Diah
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS, 2013, 35 (05): : 45 - 66
  • [25] Hardware in the loop simulation of MILP algorithm based railway traffic re-scheduling during disturbances
    Joelianto, Endra
    Setiawan, Aan
    Chaerani, Diah
    International Journal of Applied Mathematics and Statistics, 2013, 35 (05): : 45 - 66
  • [27] Evolutionary Algorithm Based on Cloud Model to Solve 3-SAT Problem
    Du, Meiyun
    Ge, Yong
    Nui, Chengshui
    Zhang, Yu-an
    2017 10TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI), 2017,
  • [28] Solving the SAT problem using a DNA computing algorithm based on ligase chain reaction
    Wang, Xiaolong
    Bao, Zhenmin
    Hu, Jingjie
    Wang, Shi
    Zhan, Aibin
    BIOSYSTEMS, 2008, 91 (01) : 117 - 125
  • [29] Solving MAX-SAT Problem by Binary Biogeograph-based Optimization Algorithm
    Ali, Hafiz Munsub
    Ejaz, Waleed
    Al Taei, May
    Iqbal, Farkhund
    2019 IEEE 10TH ANNUAL INFORMATION TECHNOLOGY, ELECTRONICS AND MOBILE COMMUNICATION CONFERENCE (IEMCON), 2019, : 1092 - 1097
  • [30] A MILP formulation and an Iterated Local Search-based algorithm for the grinding ball replacement planning problem
    de Souza, Daniel L.
    Santos, Mario S.
    Costa, Cassio P.
    Souza, Marcone J. F.
    Cota, Luciano P.
    COMPUTERS & OPERATIONS RESEARCH, 2025, 177