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Solving Nonlinear Covering Problems Arising in WLAN Design

Author

Listed:
  • Edoardo Amaldi

    (Dipartimento di Elettronica e Informazione, Politecnico di Milano, 20133 Milan, Italy)

  • Sandro Bosio

    (Institute for Operations Research, ETH Zurich, 8092 Zurich, Switzerland)

  • Federico Malucelli

    (Dipartimento di Elettronica e Informazione, Politecnico di Milano, 20133 Milan, Italy)

  • Di Yuan

    (Department of Science and Technology, Linköping University, SE-601 74 Norrköping, Sweden)

Abstract

Wireless local area networks (WLANs) are widely used for cable replacement and wireless Internet access. Because the medium access control (MAC) scheme of WLANs has a strong influence on network performance, it should be accounted for in WLAN design. This paper presents AP location models that optimize a network performance measure specifically for the MAC scheme of WLANs that represents the efficiency in sharing the wireless medium. For these models, we propose a solution framework based on an effective integer-linear programming Dantzig--Wolfe reformulation. This framework is applicable to any nonlinear covering problem where the objective function is a sum of contributions over the groundset elements (users in WLANs). Extensive computational results show that our solution strategy quickly yields optimal or near-optimal solutions for WLAN design instances of realistic size.

Suggested Citation

  • Edoardo Amaldi & Sandro Bosio & Federico Malucelli & Di Yuan, 2011. "Solving Nonlinear Covering Problems Arising in WLAN Design," Operations Research, INFORMS, vol. 59(1), pages 173-187, February.
  • Handle: RePEc:inm:oropre:v:59:y:2011:i:1:p:173-187
    DOI: 10.1287/opre.1100.0897
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    References listed on IDEAS

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    1. Marco E. Lübbecke & Jacques Desrosiers, 2005. "Selected Topics in Column Generation," Operations Research, INFORMS, vol. 53(6), pages 1007-1023, December.
    2. Geraldo Mateus & Antonio Loureiro & Ricardo Rodrigues, 2001. "Optimal Network Design for Wireless Local Area Network," Annals of Operations Research, Springer, vol. 106(1), pages 331-345, September.
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    Cited by:

    1. Erfan Mehmanchi & Andrés Gómez & Oleg A. Prokopyev, 2019. "Fractional 0–1 programs: links between mixed-integer linear and conic quadratic formulations," Journal of Global Optimization, Springer, vol. 75(2), pages 273-339, October.
    2. Alper Atamtürk & Andrés Gómez, 2020. "Submodularity in Conic Quadratic Mixed 0–1 Optimization," Operations Research, INFORMS, vol. 68(2), pages 609-630, March.
    3. Juan S. Borrero & Colin Gillen & Oleg A. Prokopyev, 2017. "Fractional 0–1 programming: applications and algorithms," Journal of Global Optimization, Springer, vol. 69(1), pages 255-282, September.
    4. Hu, Xiaoxuan & Zhu, Waiming & Ma, Huawei & An, Bo & Zhi, Yanling & Wu, Yi, 2021. "Orientational variable-length strip covering problem: A branch-and-price-based algorithm," European Journal of Operational Research, Elsevier, vol. 289(1), pages 254-269.

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