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A pseudo-polynomial heuristic for path-constrained discrete-time Markovian-target search

Cited 13 time in Web of Science Cited 17 time in Scopus
Authors
Hong, Sung-Pil; Cho, Sung-Jin; Park, Myoung-Ju
Issue Date
2009-03-01
Publisher
ELSEVIER SCIENCE BV
Citation
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH; Vol.193 2; 351-364
Keywords
Search theoryHeuristicsNetwork flowsMarkov processes
Abstract
We propose a new heuristic for the single-searcher path-constrained discrete-time Markovian-target search. The algorithm minimizes an approximate, instead of exact, nondetection probability computed from the conditional probability that reflects the search history over the time windows of a fixed length, l. Having a pseudo-polynomial complexity, it can solve, in reasonable time, the instances an order of magnitude larger than those solved in the previous studies. By an asymptotic analysis relying on the fast-mixing Markov chain, we show that the relative error of the approximation exponentially diminishes as l increases and the experimental results confirm the analysis. The experiment also reveals a correlation very close to 1 between the approximate and exact nondetection probability of a search path. This means that the heuristic produces near-optimal search paths. (C) 2007 Elsevier B.V. All rights reserved.
ISSN
0377-2217
Language
English
URI
https://hdl.handle.net/10371/75330
DOI
https://doi.org/10.1016/j.ejor.2007.10.048
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Industrial Engineering (산업공학과)Journal Papers (저널논문_산업공학과)
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