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Procedures for the evaluation of strategies for resource allocation in a stochastic environment

Published online by Cambridge University Press:  14 July 2016

K. D. Glazebrook*
Affiliation:
University of Newcastle upon Tyne
*
Postal address: Department of Mathematics and Statistics, University of Newcastle upon Tyne, NE1 7RU, UK.

Abstract

Existing procedures for strategy evaluation based on earlier work by the author have led (inter alia) to procedures for the assessment of heuristics for stochastic scheduling and to the development of an approach to sensitivity analysis. Recent theoretical work has now led to the development of more effective evaluation procedures. The key results are reported here.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1990 

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References

Bather, J. A. (1981) Randomized allocation of treatments in sequential experiments (with discussion). J. R. Statist. Soc. B 43, 265292.Google Scholar
Bergman, S. W. and Gittins, J. C. (1985) Statistical Methods for Pharmaceutical Research Planning. Marcel Dekker, New York.Google Scholar
Bruno, J. and Hofri, M. (1975) On scheduling chains of jobs on one processor with limited preemption. SIAM J. Comput. 4, 478490.Google Scholar
Gittins, J. C. and Glazebrook, K. D. (1977) On Bayesian models in stochastic scheduling. J. Appl. Prob. 14, 556565.Google Scholar
Gittins, J. C. (1979) Bandit processes and dynamic allocation indices (with discussion). J. R. Statist. Soc. B 41, 148177.Google Scholar
Glazebrook, K. D. (1978) On the optimal allocation of two or more treatments in a controlled clinical trial. Biometrika 65, 335340.Google Scholar
Glazebrook, K. D. (1982) On the evaluation of suboptimal strategies for families of alternative bandit processes. J. Appl. Prob. 19, 716722.Google Scholar
Glazebrook, K. D. (1987) Sensitivity analysis for stochastic scheduling problems. Math. Operat. Res. 12, 205223.Google Scholar
Glazebrook, K. D. and Fay, N. A. (1988) Evaluating strategies for generalized bandit problems. Internat. J. Systems Sci. 19, 16051613.Google Scholar
Katehakis, M. N. and Veinott, A. F. (1987) The multi-armed bandit problem: decomposition and computation. Math. Operat. Res. 12, 262268.CrossRefGoogle Scholar
Varaiya, P., Walrand, J. and Buyukkoc, C. (1985) Extensions of the multi-armed bandit problem: the discounted case. IEEE Trans. Autom. Control 30, 426439.Google Scholar