Heuristics for search sequencing under time-dependent probabilities of existence

Heuristics for search sequencing under time-dependent probabilities of existence

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Article ID: iaor20082444
Country: United Kingdom
Volume: 34
Issue: 7
Start Page Number: 2010
End Page Number: 2024
Publication Date: Jul 2007
Journal: Computers and Operations Research
Authors: ,
Keywords: optimization: simulated annealing, heuristics
Abstract:

We consider the problem of determining a route of a search resource to search visually multiple areas in which targets are expected to be located. It is assumed that the probability a target exists in each area is given as a result of target detection operations and that the probability decreases as time passes. It is necessary to search the areas using a search resource, and identify the exact locations of the targets. We propose heuristic algorithms including a simulated annealing (SA) algorithm for the search sequencing problem. Since the search sequence must be determined as quickly as possible not to delay the search, heuristics for search sequencing should not take too much time. We introduce a new neighborhood generation method and a new parameter for an easier control of the overall computation time in the SA algorithm. A series of computational experiments is performed for evaluating the suggested algorithms, and results are reported.

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