Allocating resources via price management systems: a dynamic programming-based approach

Forootani, Ali; Liuzza, Davide; Tipaldi, Massimo; Glielmo, Luigi

doi:10.1080/00207179.2019.1694178

Cited by 5 publications

(4 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such approach was firstly introduced by the authors in [16]. Hereafter, the main aspects of such framework are outlined along with the notation used in this manuscript.…”

Section: Preliminaries and Modelling Resource Allocation Problems As ...mentioning

confidence: 99%

“…We also provide some preliminaries on how to solve the related decision making problem via DP based techniques [7], [20]. For more details, the reader can refer to [16].…”

Section: Preliminaries and Modelling Resource Allocation Problems As ...mentioning

confidence: 99%

“…Price managers can charge different prices for the same resource over time depending on the resource availability and expected profit. As shown in [16], it is possible to formulate such price management system as a set of BDPs. In particular, there is a dedicated BDP for each feasible price (with ), which allows modelling the unpredictable behavior of customers in requesting and releasing resources.…”

Section: B Modeling Resource Allocation Problems As Mdpmentioning

confidence: 99%

“…It is considered that the same resource can be sold at different price values at different times to take the advantage of heterogeneous preferences of customers over time, e.g., a seat on an airplane or a room in a hotel. Both the formulation and the corresponding resolution for resource allocation problems with instant resource requests were firstly explored by the authors in [16], where only exact DP approaches were applied. In [17], the authors further extended the approach to incorporate the possibility that, besides an immediate allocation request, a customer can book a resource in advance for future utilisation.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Approximate dynamic programming for stochastic resource allocation problems

Forootani

Iervolino

Tipaldi

et al. 2020

IEEE/CAA J. Autom. Sinica

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Such approach was firstly introduced by the authors in [16]. Hereafter, the main aspects of such framework are outlined along with the notation used in this manuscript.…”

Section: Preliminaries and Modelling Resource Allocation Problems As ...mentioning

confidence: 99%

“…We also provide some preliminaries on how to solve the related decision making problem via DP based techniques [7], [20]. For more details, the reader can refer to [16].…”

Section: Preliminaries and Modelling Resource Allocation Problems As ...mentioning

confidence: 99%

Section: B Modeling Resource Allocation Problems As Mdpmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations