Titlebook: Optimal Stochastic Scheduling; Xiaoqiang Cai,Xianyi Wu,Xian Zhou Book 2014 Springer Science+Business Media New York 2014 Bandit Processes.

低三下四之人

Regular Performance Measures, employed in the field of stochastic scheduling, including the approach of adjacent job interchange, the argument of induction, and the approach of stochastic dynamic programming, are illustrated in this Chapter.

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Stochastic Scheduling with Incomplete Information,upying times, and the impact of incomplete information. The optimal restricted dynamic policies for this model are derived in Section 8.2 based on posterior Gittins indices. Finally, Section 8.3 discusses an interesting case in which the posterior Gittins indices can be represented by the one-step rewards rates of the jobs.

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Stochastic Machine Breakdowns,ss the optimal policies under the no-loss, total-loss and partial-loss machine breakdown models in Section 4.2–4.4, respectively. This chapter focuses on optimal static policies. Optimal dynamic policies will be introduced in Chapter 7.

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Multi-Armed Bandit Processes,, and consider open bandit processes in which infinitely many arms are allowed in Section 6.2. An extension to generalized open bandit processes is given in Section 6.3. Finally, a concise account for closed bandit processes in continuous time is presented in Section 6.4.

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0884-8289 velopments and research topics in this area.Ideal unified re.Many interesting and important results on stochastic scheduling problems have been developed in recent years, with the aid of probability theory. This book provides a comprehensive and unified coverage of studies in stochastic scheduling.

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Irregular Performance Measures,tic optimal solutions when possible, and develop solution algorithms based on the optimality properties. We will show that dynamic programming algorithms can usually be established based on V-shape properties.

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