Stochastic Algorithms for Discrete Parameter Simulation Optimization

Bhatnagar, Shalabh ; Mishra, Vivek Kumar ; Hemachandra, Nandyala (2011) Stochastic Algorithms for Discrete Parameter Simulation Optimization IEEE Transactions on Automation Science and Engineering, 8 (4). pp. 780-793. ISSN 1545-5955

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Official URL: http://doi.org/10.1109/TASE.2011.2159375

Related URL: http://dx.doi.org/10.1109/TASE.2011.2159375

Abstract

We present two efficient discrete parameter simulation optimization (DPSO) algorithms for the long-run average cost objective. One of these algorithms uses the smoothed functional approximation (SFA) procedure, while the other is based on simultaneous perturbation stochastic approximation (SPSA). The use of SFA for DPSO had not been proposed previously in the literature. Further, both algorithms adopt an interesting technique of random projections that we present here for the first time. We give a proof of convergence of our algorithms. Next, we present detailed numerical experiments on a problem of admission control with dependent service times. We consider two different settings involving parameter sets that have moderate and large sizes, respectively. On the first setting, we also show performance comparisons with the well-studied optimal computing budget allocation (OCBA) algorithm and also the equal allocation algorithm.

Item Type:Article
Source:Copyright of this article belongs to Institute of Electrical and Electronics Engineers.
Keywords:Discrete Parameter Simulation Optimization; Long-Run Average Cost Objective; Simultaneous Perturbation Stochastic Approximation; Smoothed Functional Algorithm.
ID Code:116535
Deposited On:12 Apr 2021 06:07
Last Modified:12 Apr 2021 06:07

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