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arXiv 2105.02002math.OCcs.NI
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多服务器系统中的最优定价

Optimal Pricing in Multi Server Systems

Indian Institute of Science, Bangalore(印度科学学院);Georgia Institute of Technology(佐治亚理工学院)

Ashok Krishnan K. S, Chandramani Singh, Siva Theja Maguluri, Parimal Parag

AI总结:

本文研究了多服务器系统中通过马尔可夫决策问题框架确定最优服务定价的方法,并探讨了价格与空闲服务器数量的关系及收入率的性质。

摘要:

我们研究了在客户按照再生过程到达的服务器农场中,如何确定最优的服务定价。客户具有独立且相同的(i.i.d.)指数服务时间和i.i.d.的服务估值。服务提供商旨在最大化其收入率而设定随时间变化的服务费用。如果发现有空闲服务器且服务费用低于其估值,客户将加入服务,否则将离开而不等待。我们考虑了有限和无限服务器农场的情况。我们使用马尔可夫决策问题的框架来解决最优定价问题。我们证明最优价格取决于空闲服务器的数量。我们提出了计算最优价格的算法。我们还建立了在泊松客户到达情况下的最优价格和相应收入率的若干性质。我们通过数值结果展示了所有发现。

英文摘要:

We study optimal service pricing in server farms where customers arrive according to a renewal process and have independent and identical ($i.i.d.$) exponential service times and $i.i.d.$ valuations of the service. The service provider charges a time varying service fee aiming at maximizing its revenue rate. The customers that find free servers and service fees lesser than their valuation join for the service else they leave without waiting. We consider both finite server and infinite server farms. We solve the optimal pricing problems using the framework of Markov decision problems. We show that the optimal prices depend on the number of free servers. We propose algorithms to compute the optimal prices. We also establish several properties of the optimal prices and the corresponding revenue rates in the case of Poisson customer arrivals. We illustrate all our findings via numerical results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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