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April 8, 2026INFORMS journal on computing

Multistage Mobile Anchor Redeployment in an Indoor Positioning System Using Hierarchical State Lagrangian Cut-Augmented Stochastic Dual Dynamic Integer Programming

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Authors

ZLZhongyuan LyuTCTom ChanDLDaniel P. K. Lun

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Overview

Research demonstrates a new strategy for redeploying mobile anchors to improve indoor localization efficiency, indicating significant cost reductions.

Key Points

  • This research aims to optimize the redeployment strategy for mobile anchors in indoor positioning systems, considering dynamic factors like target movement and signal conditions.
  • Developed a multistage stochastic optimization model for mobile anchor deployment.
  • Utilized a scenario tree to represent target movements and signal degradation in areas of interest.
  • Implemented hierarchical state Lagrangian cut to enhance solution speed and accuracy for large-scale instances.
  • Discounted non-line-of-sight penalties and modeled transition costs effectively.
  • Achieved over 95% reduction in the gap between lower and upper bounds compared to previous methods.
  • Proposed algorithms showed best cost performance in simulations of indoor positioning projects.
  • Demonstrated improved efficiency under the same computational time for large-scale scenarios.

Cite This Study

Lyu et al. (2026) studied this question.

synapsesocial.com/papers/69d5f13674eaea4b11a7ab6dhttps://doi.org/10.1287/ijoc.2024.0969
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