Optimized Seating Strategies for Safe and Efficient Space Utilization

DOI

10.2991/978-94-6463-950-6_37How to use a DOI?

Keywords

Seating Optimization; Social Distancing; Dynamic Programming; Stochastic Modeling; Integer Programming; Event Planning Public Safety; Benders Decomposition; Group-Based Allocation; Space Utilization

Abstract

Ensuring optimal seat allocation while maintaining safety constraints is a critical challenge in public venues and transportation systems. This study presents a data-driven approach to seating optimization, integrating dynamic assignment policies with adaptive constraints. By leveraging stochastic modeling, the framework balances occupancy efficiency with safety regulations, adjusting to fluctuating demand conditions. Simulation-based evaluations highlight the trade-offs between seat utilization and compliance, offering insights into scalable and flexible seat planning strategies for real-world applications.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Sunit Bhagwan Moorjani
PY  - 2025
DA  - 2025/12/29
TI  - Optimized Seating Strategies for Safe and Efficient Space Utilization
BT  - Proceedings of the International Conference on Smart Systems and Social Management (ICSSSM 2025)
PB  - Atlantis Press
SP  - 549
EP  - 557
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-950-6_37
DO  - 10.2991/978-94-6463-950-6_37
ID  - Moorjani2025
ER  -