In classic online resource allocation problems, a decision-maker tries to maximize her reward through making immediate and irrevocable choices regarding arriving demand points (agents). However, in many settings, some arriving agents may be patient and willing to wait a short amount of time for the resource. Motivated by this, we study the online resource allocation problem in the presence of time-flexible agents under an adversarial online arrival model. We present a setting with flexible and inflexible agents who seek a resource or service that replenishes periodically. Inflexible agents demand the resource immediately upon arrival while flexible agents are willing to wait a short period of time. Our work presents a class of POLYtope-based Resource Allocation (POLYRA) algorithms that achieve optimal or near-optimal competitive ratios under an adversarial arrival process. Such POLYRA algorithms work by consulting a particular polytope and only making decisions that guarantee the algorithm's state remains feasible in this polytope. When the number of agent types is either two or three, POLYRA algorithms can obtain the optimal competitive ratio. We design these polytopes by constructing an upper bound on the competitive ratio of any algorithm, which is characterized via a linear program (LP) that considers a collection of overlapping worst-case input sequences. Our designed POLYRA algorithms then mimic the optimal solution of this upper bound LP via its polytope's definition, obtaining the optimal competitive ratio. When there are more than three types, we show that our overlapping worst-case input sequences do not result in an attainable competitive ratio, adding an additional challenge to the problem. Considering this, we present a near-optimal nested POLYRA algorithm which achieves at least 80% of the optimal competitive ratio while having a simple and interpretable structure.
翻译:在典型的在线资源分配问题中,决策者试图通过对抵达需求点(代理商)做出即时和不可撤销的选择,使自己的回报最大化。然而,在许多环境下,一些到达的代理商可能有耐心,愿意等待很短的时间来获取资源。为此,我们研究在线资源分配问题,在具有时间灵活性的代理商面前,根据一个对抗性在线抵达模式,我们研究了在线资源分配问题。我们展示了一种灵活和不灵活、寻求定期补充资源或服务的代理商的环境。不灵活代理商在抵达时立即要求获得资源,而灵活代理商则愿意等待短期。我们的工作展示了一种基于POLYRA的基于POLYRA的资源配置(POLYRA)算法(POLYRA)算法(POLYRA)类,在对抗性抵达过程中,我们通过一个设计得最优的双轨算法(OVAL) 算法(我们目前设计最差的双轨算算法),我们通过一个最差的双轨算法(我们通过一个最差的双轨算算算算算法,然后通过一个最接近最优的流程来计算出一个最优的顶级算算法(我们最难一个最优的流程)。