Container Scheduling: Complexity and Algorithms

被引:15
|
作者
Choi, Byung-Cheon [1 ]
Lee, Kangbok [2 ]
Leung, Joseph Y. -T. [3 ]
Pinedo, Michael L. [4 ]
Briskorn, Dirk [5 ]
机构
[1] Chungnam Natl Univ, Dept Business Adm, Taejon 305704, South Korea
[2] Rutgers Business Sch, Dept Supply Chain Management & Mkt Sci, Newark, NJ 07102 USA
[3] New Jersey Inst Technol, Dept Comp Sci, Newark, NJ 07102 USA
[4] NYU, Dept Informat Operat & Management Sci, Stern Sch Business, New York, NY 10012 USA
[5] Univ Cologne, Wirtschafts & Sozialwissensch Fak, D-50923 Cologne, Germany
基金
美国国家科学基金会;
关键词
liner shipping; container allocation; on-time delivery; scheduling rules; computational complexity; OPERATIONS-RESEARCH; TIME;
D O I
10.1111/j.1937-5956.2011.01238.x
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
We consider the transport of containers through a fleet of ships. Each ship has a capacity constraint limiting the total number of containers it can carry and each ship visits a given set of ports following a predetermined route. Each container has a release date at its origination port, and a due date at its destination port. A container has a size 1 or size 2; size 1 represents a 1 TEU (20-foot equivalent unit) and size 2 represents 2 TEUs. The delivery time of a container is defined as the time when the ship that carries the container arrives at its destination port. We consider the problem of minimizing the maximum tardiness over all containers. We consider three scenarios with regard to the routes of the ships, namely, the ships having (i) identical, (ii) nested, and (iii) arbitrary routes. For each scenario, we consider different settings for origination ports, release dates, sizes of containers, and number of ports; we determine the computational complexity of various cases. We also provide a simple heuristic for some cases, with its worst case analysis. Finally, we discuss the relationship of our problems with other scheduling problems that are known to be open.
引用
收藏
页码:115 / 128
页数:14
相关论文
共 50 条
  • [1] Broadcast Scheduling: Algorithms and Complexity
    Chang, Jessica
    Erlebach, Thomas
    Gailis, Renars
    Khuller, Samir
    ACM TRANSACTIONS ON ALGORITHMS, 2011, 7 (04)
  • [2] Broadcast Scheduling: Algorithms and Complexity
    Chang, Jessica
    Erlebach, Thomas
    Gailis, Renars
    Khuller, Samir
    PROCEEDINGS OF THE NINETEENTH ANNUAL ACM-SIAM SYMPOSIUM ON DISCRETE ALGORITHMS, 2008, : 473 - +
  • [3] Container Scheduling Algorithms for Distributed Cloud Environments
    Chen, Honghua
    Shen, Cong
    Qiu, Xinyuan
    Cheng, Chuanqi
    PROCESSES, 2024, 12 (09)
  • [4] Scheduling with interference decoding: Complexity and algorithms
    Goussevskaia, O.
    Wattenhofer, R.
    AD HOC NETWORKS, 2013, 11 (06) : 1732 - 1745
  • [5] Low Complexity Scheduling Algorithms for the LTE Uplink
    Yaacoub, Elias
    Al-Asadi, Hussein
    Dawy, Zaher
    ISCC: 2009 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS, VOLS 1 AND 2, 2009, : 266 - 270
  • [6] Scheduling in reentrant robotic cells: Algorithms and complexity
    Steiner, G
    Xue, Z
    JOURNAL OF SCHEDULING, 2005, 8 (01) : 25 - 48
  • [7] Scheduling in Reentrant Robotic Cells: Algorithms and Complexity
    George Steiner
    Zhihui Xue
    Journal of Scheduling, 2005, 8 : 25 - 48
  • [8] Models and algorithms for a yard crane scheduling problem in container ports
    Vallada, Eva
    Belenguer, Jose Manuel
    Villa, Fulgencia
    Alvarez-Valdes, Ramon
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2023, 309 (02) : 910 - 924
  • [9] Discrete time model and algorithms for container yard crane scheduling
    Li, Wenkai
    Wu, Yong
    Petering, M. E. H.
    Goh, Mark
    de Souza, Robert
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2009, 198 (01) : 165 - 172
  • [10] Cyclical scheduling and multi-shift scheduling: Complexity and approximation algorithms
    Hochbaum, Dorit S.
    Levin, Asaf
    DISCRETE OPTIMIZATION, 2006, 3 (04) : 327 - 340