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Optical Engineering

Comparison of genetic algorithms and simulated annealing for cost minimization in a multisensor system
Author(s): Richard Ree Brooks; S. Sitharama Iyengar; Suresh Rai
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Paper Abstract

Many sensor fusion systems combine redundant inputs to increase information reliability. In spite of this, few studies show how to choose redundant sensors for these systems. We find sensor configurations that minimize system cost while ensuring system dependability. Dependability is the generic term for system reliability and availability. Given many types of sensors, all fulfilling system operational requirements, but with different dependability and per item cost, heuristic search methods are used to find minimum cost configurations. Our main contributions are deriving the optimization problem, showing the search can be limited to a multidimensional surface, deriving a fitness function, and providing an efficient algorithm for computing dependability bounds. Two heuristics, genetic algorithms and simulated annealing, are proposed as methods. Experimental results show cost savings of up to 20% compared to systems with only one component type.

Paper Details

Date Published: 1 February 1998
PDF: 12 pages
Opt. Eng. 37(2) doi: 10.1117/1.601639
Published in: Optical Engineering Volume 37, Issue 2
Show Author Affiliations
Richard Ree Brooks, California State Univ./Monterey Bay (United States)
S. Sitharama Iyengar, Louisiana State Univ. (United States)
Suresh Rai, Louisiana State Univ. (United States)

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