@inproceedings{8e5c28663c7446b0aaf8157dea832526,
title = "Statistical mechanics-inspired optimization for sensor field reconfiguration",
abstract = "In a multi-objective optimization scenario (e.g., optimal sensor deployment and sensor field reconfiguration for detection of moving targets), the non-dominated points are usually concentrated within a small region of the large-dimensional decision space. This paper attempts to capture the low-dimensional behavior across the Pareto front by statistical mechanics-inspired optimization tools. A location-dependent energy function has been constructed and evaluated in terms of intensive temperature-like parameters in the sense of statistical mechanics. This low-order representation has been shown to permit rapid optimization of sensor field distribution on a simulation model of undersea operations.",
author = "Kushal Mukherjee and Shalabh Gupta and Asok Ray and Wettergren, {Thomas A.}",
note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2010",
doi = "10.1109/acc.2010.5530900",
language = "English (US)",
isbn = "9781424474264",
series = "Proceedings of the 2010 American Control Conference, ACC 2010",
publisher = "IEEE Computer Society",
pages = "714--719",
booktitle = "Proceedings of the 2010 American Control Conference, ACC 2010",
address = "United States",
}