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Complexity and Online Algorithms for Minimum Skyline Coloring of Intervals

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posted on 2018-05-21, 10:07 authored by Thomas Erlebach, Fu-Hong Liu, Hsiang-Hsuan Liu, Mordechai Shalom, Prudence W. H. Wong, Shmuel Zaks
Graph coloring has been studied extensively in the literature. The classical problem concerns the number of colors used. In this paper, we focus on coloring intervals where the input is a set of intervals and two overlapping intervals cannot be assigned the same color. In particular, we are interested in the setting where there is an increasing cost associated with using a higher color index. Given a set of intervals (on a line) and a coloring, the cost of the coloring at any point is the cost of the maximum color index used at that point and the cost of the overall coloring is the integral of the cost over all points on the line. The objective is to assign a valid color to each interval and minimize the total cost of the coloring. Intuitively, the maximum color index used at each point forms a skyline and so the objective is to obtain a minimum skyline coloring. The problem arises in various applications including optical networks and job scheduling. Alicherry and Bhatia defined in 2003 a more general problem in which the colors are partitioned into classes and the cost of a color depends solely on its class. This problem is NP-hard and the reduction relies on the fact that some color class has more than one color. In this paper we show that when each color class only contains one color, this simpler setting remains NP-hard via a reduction from the arc coloring problem. In addition, we initiate the study of the online setting and present an asymptotically optimal online algorithm. We further study a variant of the problem in which the intervals are already partitioned into sets and the objective is to assign a color to each set such that the total cost is minimum. We show that this seemingly easier problem remains NP-hard by a reduction from the optimal linear arrangement problem.

Funding

T. Erlebach—Supported by a study leave granted by University of Leicester. H.-H. Liu—Partially supported by Polish National Science Centre grant 2016/22/E/ST6/00499 and partially supported by a Dual PhD studentship when the author was with University of Liverpool and National Tsing Hua University.

History

Citation

Combinatorial Optimization and Applications. COCOA 2017. Lecture Notes in Computer Science, vol 10628.

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Computer Science

Source

11th Annual International Conference on Combinatorial Optimization and Applications (COCOA'17), Shanghai

Version

  • AM (Accepted Manuscript)

Published in

Combinatorial Optimization and Applications. COCOA 2017. Lecture Notes in Computer Science

Publisher

Springer Verlag (Germany)

issn

0302-9743

isbn

978-3-319-71146-1;978-3-319-71147-8

Acceptance date

2017-09-01

Copyright date

2017

Available date

2018-05-21

Publisher version

https://link.springer.com/chapter/10.1007/978-3-319-71147-8_22

Book series

Lecture Notes in Computer Science book series (LNCS);10628

Temporal coverage: start date

2017-12-16

Temporal coverage: end date

2017-12-18

Language

en

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