Download Algorithmic Aspects in Information and Management: 10th by Qianping Gu, Pavol Hell, Boting Yang PDF

By Qianping Gu, Pavol Hell, Boting Yang

ISBN-10: 3319079557

ISBN-13: 9783319079554

ISBN-10: 3319079565

ISBN-13: 9783319079561

This quantity constitutes the lawsuits of the foreign convention on Algorithmic features in info and administration, AAIM 2014, held in Vancouver, BC, Canada, in July 2014.

The 30 revised complete papers provided including 2 invited talks have been rigorously reviewed and chosen from forty five submissions. the themes disguise such a lot components in discrete algorithms and their applications.

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Read or Download Algorithmic Aspects in Information and Management: 10th International Conference, AAIM 2014, Vancouver, BC, Canada, July 8-11, 2014. Proceedings PDF

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Additional info for Algorithmic Aspects in Information and Management: 10th International Conference, AAIM 2014, Vancouver, BC, Canada, July 8-11, 2014. Proceedings

Example text

Qh,0 (bh + k − 1) In Lemma 4, we show that ebh +k qh,0 (bh + k − 1) e · qh,0 (bh + k − 1) · ≥c = b +k−1 h qh,0 (bh + k) e qh,0 (bh + k) Competitive Algorithms for Unbounded One-Way Trading 41 for some constant c > 1 and any k ≥ 1. Thus, j k=1 ebh +k−1 ebh +j−1 1 ebh +j−1 ≤ · = O( ). qh,0 (bh + k − 1) qh,0 (bh + j − 1) 1 − 1/c qh,0 (bh + j − 1) Lemma 4. For any integer h ≥ 1 and k ≥ 1, there exist a constant c > 1, such that e · qh,0 (bh + k − 1) ≥c qh,0 (bh + k) Proof. , the increasing rate q (bh +k−1) is decreasing with the increase of x, h,0 qh,0 (bh +k) achieves the lowest value when k = 1.

And the time complexity of M M RAk is O(n2 Cnk−1 (log n)1+log k ). , the minimax regret k-sink location problem. We find several observations and facts based on which we present an O(n2 Cnk−1 (log n)1+log k ) time algorithm to solve the general problem. However, the presented algorithm is very initial. And thus, one interesting direction is to improve the presented algorithm. Another direction is to extend the problem to more general graphs, like trees. References 1. : Minimax regret 1-sink location problems in dynamic path networks.

Step 2. Compare the maximum regrets among all the Cnk−1 k-partitions and define the smallest one as the minimax regret and choose the corresponding sink locations as the optimal solution to the minimax regret k-sink problem. Obviously, M M RAk solves the minimax regret k-sink location problem based on Theorem 3 and the fact that there are Cnk−1 k-partitions in all. 2 spends O(n(log n)1+log k ) time to solve the certain k-sink Minimax Regret k-sink Location Problem 31 location problem based on Theorem 2.

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