Abstract
In the problem of online time series search introduced by El-Yaniv et al. [4], a player observes prices one by one over time and shall select exactly one of the prices on its arrival without the knowledge of future prices, aiming to maximize the selected price. In this paper, we extend the problem by introducing profit function. Considering two cases where the search duration is either known or unknown beforehand, we propose two optimal deterministic algorithms respectively. The models and results in the paper generalize those of El-Yaniv et al. [4].
The work is supported by NSF grants of China, no. 70525004, 60736027 and 70702030.
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Xu, Y., Zhang, W., Zheng, F. (2009). Optimal Algorithms for the Online Time Series Search Problem. In: Du, DZ., Hu, X., Pardalos, P.M. (eds) Combinatorial Optimization and Applications. COCOA 2009. Lecture Notes in Computer Science, vol 5573. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02026-1_30
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DOI: https://doi.org/10.1007/978-3-642-02026-1_30
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