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    Approximate dynamic programming for stochastic resource allocation problems


    Forootani, Ali and Iervolino, Raffaele and Tipaldi, Massimo and Neilson, Joshua (2020) Approximate dynamic programming for stochastic resource allocation problems. IEEE/CAA Journal of Automatica Sinica, 7 (4). pp. 975-990. ISSN 2329-9266

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    Abstract

    A stochastic resource allocation model, based on the principles of Markov decision processes (MDPs), is proposed in this paper. In particular, a general-purpose framework is developed, which takes into account resource requests for both instant and future needs. The considered framework can handle two types of reservations (i.e., specified and unspecified time interval reservation requests), and implement an overbooking business strategy to further increase business revenues. The resulting dynamic pricing problems can be regarded as sequential decision-making problems under uncertainty, which is solved by means of stochastic dynamic programming (DP) based algorithms. In this regard, Bellman’s backward principle of optimality is exploited in order to provide all the implementation mechanisms for the proposed reservation pricing algorithm. The curse of dimensionality, as the inevitable issue of the DP both for instant resource requests and future resource reservations, occurs. In particular, an approximate dynamic programming (ADP) technique based on linear function approximations is applied to solve such scalability issues. Several examples are provided to show the effectiveness of the proposed approach

    Item Type: Article
    Additional Information: Cite as: Forootani A. Approximate dynamic programming for stochastic resource allocation problems. IEEE/CAA journal of automatica sinica. 2020-07;7:975-990.
    Keywords: —Approximate dynamic programming (ADP), dynamic programming (DP); Markov decision processes (MDPs); resource allocation problem;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 16104
    Identification Number: https://doi.org/10.1109/JAS.2020.1003231
    Depositing User: Ali Forootani
    Date Deposited: 15 Jun 2022 09:22
    Journal or Publication Title: IEEE/CAA Journal of Automatica Sinica
    Publisher: IEEE Explore
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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