带出发的在线背包问题

Q4 Computer Science

Performance Evaluation Review Pub Date : 2023-06-26 DOI:10.1145/3606376.3593576

Bo Sun, Lin Yang, Mohammad Hajiesmaili, Adam Wierman, John C.S. Lui, Don Towsley, Danny H.K. Tsang

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引用次数: 0

摘要

在线背包问题是网络与运筹学中典型的在线资源分配问题。它的基本版本研究了如何将在线到达的不同大小和价值的物品打包到一个容量有限的背包中。在本文中，我们研究了一个包含物品偏离的通用版本，同时也考虑了多个背包和多维物品尺寸。我们设计了一种基于阈值的在线算法，并证明了该算法可以实现顺序最优竞争比。除了最坏情况优化算法之外，我们还提出了一种数据驱动的在线算法，该算法可以在保证最坏情况性能的同时，在典型实例下实现接近最优的平均性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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The Online Knapsack Problem with Departures

The online knapsack problem is a classic online resource allocation problem in networking and operations research. Its basic version studies how to pack online arriving items of different sizes and values into a capacity-limited knapsack. In this paper, we study a general version that includes item departures, while also considering multiple knapsacks and multi-dimensional item sizes. We design a threshold-based online algorithm and prove that the algorithm can achieve order-optimal competitive ratios. Beyond worst-case optimized algorithms, we also propose a data-driven online algorithm that can achieve near-optimal average performance under typical instances while guaranteeing the worst-case performance.

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来源期刊

Performance Evaluation Review Computer Science-Computer Networks and Communications

CiteScore

1.00

自引率

0.00%

发文量

193