Hierarchical Seating Allocation (Extended Abstract)

The Hierarchical Seating Allocation Problem (HSAP) is the problem to allocate an organizational hierarchy of teams to a set of seats on a floor plan. This problem is driven by the necessity for large organizations with large hierarchies to ensure that teams with close hierarchical relationships are seated in proximity to one another, such as ensuring a research group occupies a contiguous area. Currently, this problem is managed manually leading to infrequent and suboptimal replanning efforts. To alleviate this manual process, we propose an end-to-end framework to solve the HSAP. A scalable approach to calculate the distance between any pair of seats using a probabilistic road map (PRM) and rapidly-exploring random trees (RRT) which is combined with heuristic search and dynamic programming approach to solve the HSAP using integer programming. We demonstrate our approach under different sized instances by evaluating the PRM framework and subsequent allocations both quantitatively and qualitatively.

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Publication Details

Journal
Proceedings of the International Symposium on Combinatorial Search
Published
2025-07-20
DOI
https://doi.org/10.1609/socs.v18i1.36009
Primary Topic
Ergonomics and Musculoskeletal Disorders
Type
article
Field-Weighted Citation Impact
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article

Hierarchical Seating Allocation (Extended Abstract)

Parisa Zehtabi, Nicolás Marchesotti, Daniele Magazzeni, Michael Cashmore et al.
Proceedings of the International Symposium on Combinatorial Search
Ergonomics and Musculoskeletal Disorders
article

Hierarchical Seating Allocation (Extended Abstract)

Parisa Zehtabi, Nicolás Marchesotti, Daniele Magazzeni, Michael Cashmore, Manuela Veloso, Anton Ipsen, Kirsty Fielding
article en

Abstract

The Hierarchical Seating Allocation Problem (HSAP) is the problem to allocate an organizational hierarchy of teams to a set of seats on a floor plan. This problem is driven by the necessity for large organizations with large hierarchies to ensure that teams with close hierarchical relationships are seated in proximity to one another, such as ensuring a research group occupies a contiguous area. Currently, this problem is managed manually leading to infrequent and suboptimal replanning efforts. To alleviate this manual process, we propose an end-to-end framework to solve the HSAP. A scalable approach to calculate the distance between any pair of seats using a probabilistic road map (PRM) and rapidly-exploring random trees (RRT) which is combined with heuristic search and dynamic programming approach to solve the HSAP using integer programming. We demonstrate our approach under different sized instances by evaluating the PRM framework and subsequent allocations both quantitatively and qualitatively.

Proceedings of the International Symposium on Combinatorial SearchVol. 18
JPMorgan Chase & Co (United States) (US)
Openalex Percentile: Top 79%
Ergonomics and Musculoskeletal Disorders
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