IDEAS home Printed from https://ideas.repec.org/a/taf/oabmxx/v6y2019i1p1616351.html
   My bibliography  Save this article

Metaheuristic algorithm for ship routing and scheduling problems with time window

Author

Listed:
  • Khaled Alhamad
  • Azizah Alrashidi
  • Sameh Alkharashi

Abstract

This paper describes a Tabu Search (TS) heuristic for a Ship Routing and Scheduling Problem (SRSP). The method was developed to address the problem of loading cargos for many customers using heterogeneous ships. Constraints include delivery time windows imposed by customers, the time horizon by which all deliveries must be made, and ship capacities. The proposed algorithm aims to minimize the overall cost of shipping operation without any violations. The TS algorithm is compared with a similar method that uses the Set Partitioning Problem (SPP) in terms of solution quality and computational time. The results of a computational investigation are presented. Solution quality and execution time are explored with respect to problem size and parameters controlling the TS such neighborhood size. It is found that while the SPP method solves small-scale problems efficiently, treating large-scale problems with this method becomes complicated due to computational problems; however, the TS method can overcome this challenge. Furthermore, TS consistently returns near-optimal solution within a reasonable time.

Suggested Citation

  • Khaled Alhamad & Azizah Alrashidi & Sameh Alkharashi, 2019. "Metaheuristic algorithm for ship routing and scheduling problems with time window," Cogent Business & Management, Taylor & Francis Journals, vol. 6(1), pages 1616351-161, January.
    • Handle: RePEc:taf:oabmxx:v:6:y:2019:i:1:p:1616351
    DOI: 10.1080/23311975.2019.1616351
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/23311975.2019.1616351
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/23311975.2019.1616351?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Khaled Alhamad & Yousuf Alkhezi & M. F. Alhajri, 2022. "Nonlinear Integer Programming for Solving Preventive Maintenance Scheduling Problem for Cogeneration Plants with Production," Sustainability, MDPI, vol. 15(1), pages 1-18, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:oabmxx:v:6:y:2019:i:1:p:1616351. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://cogentoa.tandfonline.com/OABM20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.