Statistical mechanics-inspired optimization for sensor field reconfiguration

Kushal Mukherjee, Shalabh Gupta, Asok Ray, Thomas A. Wettergren

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 2010 American Control Conference, ACC 2010
PublisherIEEE Computer Society
Pages714-719
Number of pages6
ISBN (Print)9781424474264
DOIs
StatePublished - 2010

Publication series

NameProceedings of the 2010 American Control Conference, ACC 2010

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

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