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Online Knapsack of Unknown Capacity: Energy Optimization for Smartphone Communications

机译:在线容量未知的背包:智能手机通信的能源优化

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We propose a new variant of the more standard online knapsack problem where the only information missing to the provided instances is the capacity B of the knapsack. We refer to this problem as the online Knapsack of Unknown Capacity problem. Any algorithm must provide a strategy for ordering the items that are inserted in the knapsack in an online fashion, until the actual capacity of the knapsack is revealed and the last inserted item might not fit in. Apart from the interest in a new version of the fundamental knapsack problem, the motivations that lead to define this new variant come from energy consumption constraints in smartphone communications. We do provide lower and upper bounds to the problem for various cases. In general, we design an optimal algorithm admitting a 1/2-competitive ratio. When all items admit uniform ratio of profit over size, our algorithm provides a 49/86 = .569... competitive ratio that leaves some gap with the provided bound of 1/Φ = .618..., the inverse of the golden number. We then conduct experimental analysis for the competitive ratio guaranteed algorithms compared to the optimum and to various heuristics.
机译:我们提出了更标准的在线背包问题的新变体,其中所提供的实例唯一缺少的信息是背包的容量B。我们将此问题称为未知容量的在线背包问题。任何算法都必须提供一种策略,以在线方式订购插入背包的物品,直到揭示背包的实际容量并且最后一个插入的物品可能不适合为止。基本的背包问题,导致定义此新变体的动机来自智能手机通信中的能耗限制。我们确实为各种情况提供了该问题的上下限。通常,我们设计一种允许1/2竞争比率的最佳算法。当所有项目都接受利润与规模的统一比率时,我们的算法将提供49/86 = .569 ...竞争比率,与提供的边界1 /Φ= .618 ...相比,存在一定的差距,这是黄金的倒数数字。然后,我们对与最优比率和各种启发式算法相比的竞争率保证算法进行实验分析。

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