IDEAS home Printed from https://ideas.repec.org/a/spr/jglopt/v79y2021i3d10.1007_s10898-020-00953-5.html
   My bibliography  Save this article

Efficient computation of minimum-area rectilinear convex hull under rotation and generalizations

Author

Listed:
  • Carlos Alegría

    (Università Roma Tre)

  • David Orden

    (Universidad de Alcalá)

  • Carlos Seara

    (Universitat Politècnica de Catalunya)

  • Jorge Urrutia

    (Universidad Nacional Autónoma de México)

Abstract

Let P be a set of n points in the plane. We compute the value of $$\theta \in [0,2\pi )$$ θ ∈ [ 0 , 2 π ) for which the rectilinear convex hull of P, denoted by $$\mathcal {RH}_{P}({\theta })$$ RH P ( θ ) , has minimum (or maximum) area in optimal $$O(n\log n)$$ O ( n log n ) time and O(n) space, improving the previous $$O(n^2)$$ O ( n 2 ) bound. Let $$\mathcal {O}$$ O be a set of k lines through the origin sorted by slope and let $$\alpha _i$$ α i be the sizes of the 2k angles defined by pairs of two consecutive lines, $$i=1, \ldots , 2k$$ i = 1 , … , 2 k . Let $$\Theta _{i}=\pi -\alpha _i$$ Θ i = π - α i and $$\Theta =\min \{\Theta _i :i=1,\ldots ,2k\}$$ Θ = min { Θ i : i = 1 , … , 2 k } . We obtain: (1) Given a set $$\mathcal {O}$$ O such that $$\Theta \ge \frac{\pi }{2}$$ Θ ≥ π 2 , we provide an algorithm to compute the $$\mathcal {O}$$ O -convex hull of P in optimal $$O(n\log n)$$ O ( n log n ) time and O(n) space; If $$\Theta

Suggested Citation

  • Carlos Alegría & David Orden & Carlos Seara & Jorge Urrutia, 2021. "Efficient computation of minimum-area rectilinear convex hull under rotation and generalizations," Journal of Global Optimization, Springer, vol. 79(3), pages 687-714, March.
  • Handle: RePEc:spr:jglopt:v:79:y:2021:i:3:d:10.1007_s10898-020-00953-5
    DOI: 10.1007/s10898-020-00953-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10898-020-00953-5
    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/s10898-020-00953-5?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. Griffiths, Valeriya & Scanlan, James P. & Eres, Murat H. & Martinez-Sykora, Antonio & Chinchapatnam, Phani, 2019. "Cost-driven build orientation and bin packing of parts in Selective Laser Melting (SLM)," European Journal of Operational Research, Elsevier, vol. 273(1), pages 334-352.
    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. Pablo Pérez-Lantero & Carlos Seara & Jorge Urrutia, 2024. "Rectilinear convex hull of points in 3D and applications," Journal of Global Optimization, Springer, vol. 90(2), pages 551-571, October.
    2. Carlos Alegría & David Orden & Carlos Seara & Jorge Urrutia, 2023. "Separating bichromatic point sets in the plane by restricted orientation convex hulls," Journal of Global Optimization, Springer, vol. 85(4), pages 1003-1036, April.
    3. Kieu Linh, Nguyen & Thanh An, Phan & Van Hoai, Tran, 2022. "A fast and efficient algorithm for determining the connected orthogonal convex hulls," Applied Mathematics and Computation, Elsevier, vol. 429(C).

    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. Altekin, F. Tevhide & Bukchin, Yossi, 2022. "A multi-objective optimization approach for exploring the cost and makespan trade-off in additive manufacturing," European Journal of Operational Research, Elsevier, vol. 301(1), pages 235-253.
    2. Gahm, Christian & Uzunoglu, Aykut & Wahl, Stefan & Ganschinietz, Chantal & Tuma, Axel, 2022. "Applying machine learning for the anticipation of complex nesting solutions in hierarchical production planning," European Journal of Operational Research, Elsevier, vol. 296(3), pages 819-836.
    3. Marić, Josip & Opazo-Basáez, Marco & Vlačić, Božidar & Dabić, Marina, 2023. "Innovation management of three-dimensional printing (3DP) technology: Disclosing insights from existing literature and determining future research streams," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    4. Jose M. Framinan & Paz Perez-Gonzalez & Victor Fernandez-Viagas, 2023. "An overview on the use of operations research in additive manufacturing," Annals of Operations Research, Springer, vol. 322(1), pages 5-40, March.

    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:jglopt:v:79:y:2021:i:3:d:10.1007_s10898-020-00953-5. 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.