S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Industrial Engineering (산업공학과) Journal Papers (저널논문_산업공학과)
Optimal search-relocation trade-off in Markovian-target searching
Cited 17 time in Web of Science Cited 26 time in Scopus
- Issue Date
- Computers & Operations Research 2009;36:2097-2104
- Optimization ; Search ; Networks and graphs ; Probability
- In this study, a standard moving-target search model was extended with a multiple-search-speed option, whereby a trade-off is enabled between the increased detection chances owing to the searcher's better location and the increased uncertainty of the target's location resulting from the diminished search performance incurred in the relocation. This enhances the detection probability of the output search path and, thereby, the model's practicality. However, the scalability of the solution method is essential to its implementation, as the basic model is already NP-hard. We developed an efficient heuristic by combining the idea of approximate nondetection probability minimization and a hybridized shortest-path heuristic that exploits the fast-mixing property of the Markov chain. According to the results of an intensive experiment, the heuristic achieves a near-optimal trade-off within a very reasonable computation time.
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