Moment-based approximations for stochastic control model of type (s, S)

Aslı Bektaş Kamışlık, Feyrouz Baghezze, Tulay Kesemen and Tahir Khaniyev

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 21, 7505-7516

Abstract: In this study, we propose an approximation for a renewal reward process that describes a stochastic control model of type (s, S) based on the first three moments of demand random variables. Various asymptotic expansions for this model exist in the literature. All these studies rely on the condition of knowing the distribution function of demand random variables and require obtaining the asymptotic expansion of the renewal function produced by them. However, obtaining a renewal function can be challenging for certain distribution families, and in some cases, the mathematical structure of the renewal function is difficult to apply. Therefore, in this study, simple and compact approximations are presented for the stochastic control model of type (s, S). The findings of this study rely on Kambo’s method, through which we obtain approximations for the ergodic distribution, and the nth order ergodic moments of this process. To conclude the study, the accuracy of the proposed approximate formulas are examined through a specialized illustrative example. Moreover, it has been noted that the proposed approximation is more accurate than the approximations existing in the literature.

Date: 2024
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DOI: 10.1080/03610926.2023.2268765

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