IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v289y2020i2d10.1007_s10479-019-03327-7.html
   My bibliography  Save this article

Technical note: the expected length of an orderly path

Author

Listed:
  • Heather S. Lutz

    (Penn State University)

  • Trevor S. Hale

    (Texas A&M University)

  • Faizul Huq

    (Ohio University)

Abstract

Logistics planners often need to estimate length of a path through n random points. The problem has connections to geographical surveys, Steiner tree problems, traveling salesman problems, Amazon.com and Alibaba.cn drone aircraft multi-package outbound delivery paths, and aircraft sorties. In this effort, we utilize two applied probability tenets in concert to derive a closed form model for the expected distance between orderly pairs of randomly distributed delivery locations across some region. Indeed, by themselves each of the two tenets offer little help but when utilized simultaneously they elucidate the problem. Then, this expected distance is multiplied by (n − 1) to estimate the total length of the associated orderly path (albeit not the optimal path) through the n points. This total path length estimate, in turn, provides decision makers with a better information for distribution and logistics planning.

Suggested Citation

  • Heather S. Lutz & Trevor S. Hale & Faizul Huq, 2020. "Technical note: the expected length of an orderly path," Annals of Operations Research, Springer, vol. 289(2), pages 463-472, June.
  • Handle: RePEc:spr:annopr:v:289:y:2020:i:2:d:10.1007_s10479-019-03327-7
    DOI: 10.1007/s10479-019-03327-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03327-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-019-03327-7?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.

    References listed on IDEAS

    as
    1. Morganna Carmem Diniz & Edmundo de Souza e Silva & H. Richard Gail, 2002. "Calculating the Distribution of a Linear Combination of Uniform Order Statistics," INFORMS Journal on Computing, INFORMS, vol. 14(2), pages 124-131, May.
    2. Rodney Vaughan, 1984. "Approximate Formulas for Average Distances Associated with Zones," Transportation Science, INFORMS, vol. 18(3), pages 231-244, August.
    3. Barreto,Humberto & Howland,Frank, 2006. "Introductory Econometrics," Cambridge Books, Cambridge University Press, number 9780521843195.
    4. S. Lin & B. W. Kernighan, 1973. "An Effective Heuristic Algorithm for the Traveling-Salesman Problem," Operations Research, INFORMS, vol. 21(2), pages 498-516, April.
    5. Trevor S. Hale & Faizul Huq & Heather Lutz & Carles Moslares, 2015. "On the expected distance of a random walk," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 7(3), pages 241-250.
    Full references (including those not matched with items on IDEAS)

    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. Elza Jurun & Snježana Pivac, 2011. "Comparative regional GDP analysis: case study of Croatia," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(3), pages 319-335, September.
    2. Ahmed Kheiri & Alina G. Dragomir & David Mueller & Joaquim Gromicho & Caroline Jagtenberg & Jelke J. Hoorn, 2019. "Tackling a VRP challenge to redistribute scarce equipment within time windows using metaheuristic algorithms," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 561-595, December.
    3. Anurag Agarwal, 2009. "Theoretical insights into the augmented-neural-network approach for combinatorial optimization," Annals of Operations Research, Springer, vol. 168(1), pages 101-117, April.
    4. Mutsunori Yagiura & Toshihide Ibaraki & Fred Glover, 2004. "An Ejection Chain Approach for the Generalized Assignment Problem," INFORMS Journal on Computing, INFORMS, vol. 16(2), pages 133-151, May.
    5. Aritra Pal & Hadi Charkhgard, 2019. "A Feasibility Pump and Local Search Based Heuristic for Bi-Objective Pure Integer Linear Programming," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 115-133, February.
    6. Zi-bin Jiang & Qiong Yang, 2016. "A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-15, November.
    7. Stefan Poikonen & Bruce Golden, 2020. "The Mothership and Drone Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 249-262, April.
    8. Jung, Jung Woo & Lee, Young Hae, 2010. "Heuristic algorithms for production and transportation planning through synchronization of a serial supply chain," International Journal of Production Economics, Elsevier, vol. 124(2), pages 433-447, April.
    9. R Torres-Velázquez & V Estivill-Castro, 2004. "Local search for Hamiltonian Path with applications to clustering visitation paths," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(7), pages 737-748, July.
    10. Luca Quadrifoglio & Randolph W. Hall & Maged M. Dessouky, 2006. "Performance and Design of Mobility Allowance Shuttle Transit Services: Bounds on the Maximum Longitudinal Velocity," Transportation Science, INFORMS, vol. 40(3), pages 351-363, August.
    11. Luca Maria Gambardella & Marco Dorigo, 2000. "An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem," INFORMS Journal on Computing, INFORMS, vol. 12(3), pages 237-255, August.
    12. Paolo Gianessi & Laurent Alfandari & Lucas Létocart & Roberto Wolfler Calvo, 2016. "The Multicommodity-Ring Location Routing Problem," Transportation Science, INFORMS, vol. 50(2), pages 541-558, May.
    13. Rego, Cesar & Roucairol, Catherine, 1995. "Using Tabu search for solving a dynamic multi-terminal truck dispatching problem," European Journal of Operational Research, Elsevier, vol. 83(2), pages 411-429, June.
    14. Wayne Desarbo, 1982. "Gennclus: New models for general nonhierarchical clustering analysis," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 449-475, December.
    15. Xuanjing Fang & Yanan Du & Yuzhuo Qiu, 2017. "Reducing Carbon Emissions in a Closed-Loop Production Routing Problem with Simultaneous Pickups and Deliveries under Carbon Cap-and-Trade," Sustainability, MDPI, vol. 9(12), pages 1-15, November.
    16. E A Silver, 2004. "An overview of heuristic solution methods," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(9), pages 936-956, September.
    17. Karen Aardal & Cor Hurkens & Jan Karel Lenstra & Sergey Tiourine, 2002. "Algorithms for Radio Link Frequency Assignment: The Calma Project," Operations Research, INFORMS, vol. 50(6), pages 968-980, December.
    18. Ghosh, Diptesh, 2016. "Exploring Lin Kernighan neighborhoods for the indexing problem," IIMA Working Papers WP2016-02-13, Indian Institute of Management Ahmedabad, Research and Publication Department.
    19. Wex, Felix & Schryen, Guido & Feuerriegel, Stefan & Neumann, Dirk, 2014. "Emergency response in natural disaster management: Allocation and scheduling of rescue units," European Journal of Operational Research, Elsevier, vol. 235(3), pages 697-708.
    20. Katayama, Kengo & Narihisa, Hiroyuki, 2001. "Performance of simulated annealing-based heuristic for the unconstrained binary quadratic programming problem," European Journal of Operational Research, Elsevier, vol. 134(1), pages 103-119, October.

    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:spr:annopr:v:289:y:2020:i:2:d:10.1007_s10479-019-03327-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.