Structured Design

Get Algorithmic Aspects in Information and Management: 10th PDF

By Qianping Gu, Pavol Hell, Boting Yang

ISBN-10: 3319079557

ISBN-13: 9783319079554

ISBN-10: 3319079565

ISBN-13: 9783319079561

This quantity constitutes the complaints of the overseas convention on Algorithmic points in details 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 subjects disguise such a lot components in discrete algorithms and their applications.

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

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Then, for any input price sequence with highest value p∗ , our algorithm will have revenue at least δ1 + 2δ2 + ... + p∗ δ ∗ ≥ (p∗ )2 δ ∗ /2, and since no algorithm (including the offline optimal algorithm) can have revenue higher than p∗ , the competitive ratio of this algorithm is O(1/(p∗ δ ∗ )) (Lemma 1). Now we give the algorithm. , i−1 f (x)dx = δi . e. prices at which the seller sells some (non-zero) amount to the buyer. , p∗ /p1 ) where the first price r1 is 1 and the normalized maximum r∗ is the ratio of the highest transacted price p∗ to the lowest transacted price p1 .

Chin et al. possible buyer with higher price may not come. Thus, to have a good performance, the amount sold and the amount remaining should be balanced nicely. For the purposes of illustrating the main ideas of our algorithm only, consider the case when all prices are non-negative integers; in general, our algorithm is not restricted to integer prices. We make the following observations. – Our algorithm should only sell products when the price is strictly higher than the maximum price that we have seen so far.

Based on Theorem 3 and algorithm BSAk , we design an algorithm M M RAk solving minimax regret k-sink problem as follows. MiniMax-Regret-Algorithm M M RAk : Step 1. 1. Under any worst case scenario s ∈ SL ∪ SR , compute the evacuation time of P T k , Θ(P T k , s). 2. Solve the certain k-sink location problem under the same scenario s based on algorithm BSAk . And compute the optimal evacuation time, Θ(P T opt (s), s). 3. Define the regret of P T k under s as R(P T k , s) = Θ(P T k , s) − Θ(P T opt (s), s).

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Algorithmic Aspects in Information and Management: 10th International Conference, AAIM 2014, Vancouver, BC, Canada, July 8-11, 2014. Proceedings by Qianping Gu, Pavol Hell, Boting Yang


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