Optimization of Access Point Location Using an Integer Programming Model

To address the increasing demand for reliable connectivity in educational environments, strategic access point (AP) placement is necessary to support coverage and bandwidth requirements while controlling installation cost. This study applies a binary integer programming model to the third floor of the College of Technologies at Bukidnon State University in order to determine a feasible minimum-cost AP configuration under site-specific conditions. The model incorporates coverage, bandwidth, range, and AP-count constraints, together with demand estimates based on expected simultaneous network use. Results show that the optimization framework can identify a feasible AP-to-area assignment that satisfies the imposed constraints within the study site. Because the nominal AP ranges are large relative to the dimensions of the floor, the resulting configuration is influenced more strongly by installation cost and bandwidth feasibility than by range limitation alone. The findings show the practical value of binary integer programming as a structured planning tool for access point placement in bounded indoor environments. While the resulting configuration is specific to the physical, technical, and cost conditions of the study area, the modeling approach may be applied to other institutional settings through appropriate parameter recalibration. A post-deployment wireless site survey is recommended to verify actual field performance and identify any remaining coverage gaps.

@article{Panes2026,
  title     = {Optimization of Access Point Location Using an Integer Programming Model},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {4},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Joan Marie M. Panes and Marilou O. Espina and Jovelin M. Lapates},
  doi       = {10.14569/IJACSA.2026.0170451},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170451}
}