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Competitive analysis for discrete multiple online rental problems

机译:离散多个在线租赁问题的竞争分析

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摘要

Many actual rental activities present online rental problems with multiple units of assets or equipment whose use can be continuous,separable,or discrete.Using online algorithms and competitive analysis,continuous multiple online rental problems have obtained the optimal risk control strategy and the optimal competitive ratio.For multiple online rental problems with discrete assets,first,we present an approximation algorithm for a risk control strategy and the upper bound of the optimal competitive ratio.Moreover,in practical applications,the approximation algorithm of the discrete online problem provides the approximate rental quantities in each period and the solution principle for the approximate competitive ratio.Second,we present the approximate optimal rental quantities and the correction algorithm to obtain a better competitive ratio based on the approximation algorithm.Finally,we compare the approximation algorithm with the correction algorithm by real data.Our findings show that when the approximate solution is used to replace the corrected solution,the resulting approximation error is usually less than the magnitude of 1/ms where m is the total units of certain assets or equipment and s is the price to buy one unit in each period.
机译:许多实际的租赁活动存在于在线租赁问题,这些资产或设备的多个资产问题可以连续,可分离或离散。在线算法和竞争性分析,连续多个在线租赁问题已获得最佳风险控制策略和最佳竞争比率。对于多个在线租赁问题,首先,我们提出了一种风险控制策略的近似算法和最佳竞争比率的上限。在实际应用中,离散在线问题的近似算法提供了近似的租金每个时期的数量和近似竞争比例的解决方案原则。二进制,我们介绍了基于近似算法获得更好的竞争比率的近似最优租赁量和校正算法。最后,我们将近似算法与校正算法进行比较通过真实的数据。我们调查结果显示在使用近似解决方案来替换校正的解决方案时,产生的近似误差通常小于1 / ms的幅度,其中M是某些资产或设备的总单元,并且S是在每个时期购买一个单位的价格。

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