IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v7y2019i4p359-d224458.html
   My bibliography  Save this article

A Hybrid Framework Combining Genetic Algorithm with Iterated Local Search for the Dominating Tree Problem

Author

Listed:
  • Shuli Hu

    (School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

  • Huan Liu

    (School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

  • Xiaoli Wu

    (School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

  • Ruizhi Li

    (School of Management Science and Information Engineering, Jilin University of Finance and Economics, Changchun 130117, China)

  • Junping Zhou

    (School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

  • Jianan Wang

    (School of Computer Science and Information Technology, Northeast Normal University, Changchun 130117, China)

Abstract

Given an undirected, connected and edge-weighted graph, the dominating tree problem consists of finding a tree with minimum total edge weight such that for each vertex is either in the tree or adjacent to a vertex in the tree. In this paper, we propose a hybrid framework combining genetic algorithm with iterated local search (GAITLS) for solving the dominating tree problem. The main components of our framework are as follows: (1) the score functions D s c o r e and W s c o r e applied in the initialization and local search phase; (2) the initialization procedure with restricted candidate list (RCL) by controlling the parameter to balance the greediness and randomness; (3) the iterated local search with three phases, which is used to intensify the individuals; (4) the mutation with high diversity proposed to perturb the population. The experimental results on the classical instances show that our method performs much better than the-state-of-art algorithms.

Suggested Citation

  • Shuli Hu & Huan Liu & Xiaoli Wu & Ruizhi Li & Junping Zhou & Jianan Wang, 2019. "A Hybrid Framework Combining Genetic Algorithm with Iterated Local Search for the Dominating Tree Problem," Mathematics, MDPI, vol. 7(4), pages 1-14, April.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:4:p:359-:d:224458
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/7/4/359/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/7/4/359/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yannis Marinakis & Athanasios Migdalas & Panos M. Pardalos, 2005. "A Hybrid Genetic—GRASP Algorithm Using Lagrangean Relaxation for the Traveling Salesman Problem," Journal of Combinatorial Optimization, Springer, vol. 10(4), pages 311-326, December.
    2. Michael F. Argüello & Jonathan F. Bard & Gang Yu, 1997. "A Grasp for Aircraft Routing in Response to Groundings and Delays," Journal of Combinatorial Optimization, Springer, vol. 1(3), pages 211-228, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Ze Pan & Xinyun Wu & Caiquan Xiong, 2023. "Dual-Neighborhood Search for Solving the Minimum Dominating Tree Problem," Mathematics, MDPI, vol. 11(19), pages 1-20, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kyriakakis, Nikolaos A. & Marinaki, Magdalene & Matsatsinis, Nikolaos & Marinakis, Yannis, 2022. "A cumulative unmanned aerial vehicle routing problem approach for humanitarian coverage path planning," European Journal of Operational Research, Elsevier, vol. 300(3), pages 992-1004.
    2. Zhao, Ai & Bard, Jonathan F. & Bickel, J. Eric, 2023. "A two-stage approach to aircraft recovery under uncertainty," Journal of Air Transport Management, Elsevier, vol. 111(C).
    3. Sinclair, Karine & Cordeau, Jean-François & Laporte, Gilbert, 2014. "Improvements to a large neighborhood search heuristic for an integrated aircraft and passenger recovery problem," European Journal of Operational Research, Elsevier, vol. 233(1), pages 234-245.
    4. Abdelghany, Khaled F. & Abdelghany, Ahmed F. & Ekollu, Goutham, 2008. "An integrated decision support tool for airlines schedule recovery during irregular operations," European Journal of Operational Research, Elsevier, vol. 185(2), pages 825-848, March.
    5. Delgado, Felipe & Sirhan, Cristóbal & Katscher, Mathias & Larrain, Homero, 2020. "Recovering from demand disruptions on an air cargo network," Journal of Air Transport Management, Elsevier, vol. 85(C).
    6. Başdere, Mehmet & Bilge, Ümit, 2014. "Operational aircraft maintenance routing problem with remaining time consideration," European Journal of Operational Research, Elsevier, vol. 235(1), pages 315-328.
    7. Jian Yang & Xiangtong Qi & Gang Yu, 2005. "Disruption management in production planning," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(5), pages 420-442, August.
    8. Thengvall, Benjamin G. & Yu, Gang & Bard, Jonathan F., 2001. "Multiple fleet aircraft schedule recovery following hub closures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(4), pages 289-308, May.
    9. Huang, Zhouchun & Luo, Xiaodong & Jin, Xianfei & Karichery, Sureshan, 2022. "An iterative cost-driven copy generation approach for aircraft recovery problem," European Journal of Operational Research, Elsevier, vol. 301(1), pages 334-348.
    10. Scott E. Atkinson & Kamalini Ramdas & Jonathan W. Williams, 2016. "Robust Scheduling Practices in the U.S. Airline Industry: Costs, Returns, and Inefficiencies," Management Science, INFORMS, vol. 62(11), pages 3372-3391, November.
    11. Derui Wang & Yanfeng Wu & Jian-Qiang Hu & Miaomiao Liu & Peiwen Yu & Cheng Zhang & Yan Wu, 2019. "Flight Schedule Recovery: A Simulation-Based Approach," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(06), pages 1-19, December.
    12. G Zhu & J F Bard & G Yu, 2005. "Disruption management for resource-constrained project scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(4), pages 365-381, April.

    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:gam:jmathe:v:7:y:2019:i:4:p:359-:d:224458. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.