72 research outputs found

    Tight bounds for NF-based bounded-space online bin packing algorithms

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    In Zheng et al. (J Comb Optim 30(2):360–369, 2015) modelled a surgery problem by the one-dimensional bin packing, and developed a semi-online algorithm to give an efficient feasible solution. In their algorithm they used a buffer to temporarily store items, having a possibility to lookahead in the list. Because of the considered practical problem they investigated the 2-parametric case, when the size of the items is at most 1/2. Using an NF-based online algorithm the authors proved an ACR of 13/9 = 1.44 … for any given buffer size not less than 1. They also gave a lower bound of 4/3 = 1.33 … for the bounded-space algorithms that use NF-based rules. Later, in Zhang et al. (J Comb Optim 33(2):530–542, 2017) an algorithm was given with an ACR of 1.4243, and the authors improved the lower bound to 1.4230. In this paper we present a tight lower bound of h∞ (r) for the r-parametric problem when the buffer capacity is 3. Since h∞ (2) = 1.42312 …, our result—as a special case—gives a tight bound for the algorithm-class given in 2017. To prove that the lower bound is tight, we present an NF-based online algorithm that considers the r-parametric problem, and uses a buffer with capacity of 3. We prove that this algorithm has an ACR that is equal to the lower bounds for arbitrary r. © Springer Science+Business Media, LLC 2017

    Regional multicriteria and multimodal route planning system for public transportation : a case study

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    Nowadays, the use of computer-based route planners is popular among private and public transportation passengers. A large range of websites and GPS navigation devices provide such services for their users. Here, we present an algorithm used by a route planning system which operates on a complete public transport network of two regions from two countries, namely Hungary and Serbia. The algorithm can handle the pedestrian traffic between stops not too far from each other. It can take into account individual user preferences like walking distances and modes of transport. The graph representing the transport network was very large, but with the help of some speed-up techniques, we managed to create an effective search algorithm that is able to handle user requirements

    Bounds for online bin packing with cardinality constraints

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    Abstract We study a bin packing problem in which a bin can contain at most k items of total size at most 1, where k ≥ 2 is a given parameter. Items are presented one by one in an online fashion. We analyze the best absolute competitive ratio of the problem and prove tight bounds of 2 for any k ≥ 4 . Additionally, we present bounds for relatively small values of k with respect to the asymptotic competitive ratio and the absolute competitive ratio. In particular, we provide tight bounds on the absolute competitive ratio of First Fit for k = 2 , 3 , 4 , and improve the known lower bounds on asymptotic competitive ratios for multiple values of k. Our method for obtaining a lower bound on the asymptotic competitive ratio using a certain type of an input is general, and we also use it to obtain an alternative proof of the known lower bound on the asymptotic competitive ratio of standard online bin packing
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