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DALIAN UNIVERSITY OF TECHNOLOGY Login 中文
Xin Han

Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates


Main positions:Professor
Gender:Male
Alma Mater:Kyoto University
Degree:Doctoral Degree
School/Department:Software School
Discipline:Computer Software and Theory. Operation Research and Control Theory
Contact Information:hanxin@dlut.edu.cn 0086-411-62274404
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Current position: Home >> Scientific Research >> Paper Publications

A New Upper Bound 2.5545 on 2D Online Bin Packing

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Indexed by:期刊论文

Date of Publication:2011-09-01

Journal:ACM TRANSACTIONS ON ALGORITHMS

Included Journals:Scopus、SCIE、EI

Volume:7

Issue:4

ISSN No.:1549-6325

Key Words:Online algorithms; bin packing problems; competitive ratio

Abstract:The 2D Online Bin Packing is a fundamental problem in Computer Science and the determination of its asymptotic competitive ratio has research attention. In a long series of papers, the lower bound of this ratio has been improved from 1.808, 1.856 to 1.907 and its upper bound reduced from 3.25, 3.0625, 2.8596, 2.7834 to 2.66013. In this article, we rewrite the upper bound record to 2.5545. Our idea for the improvement is as follows.
   In 2002, Seiden and van Stee [Seiden and van Stee 2003] proposed an elegant algorithm called H. C, comprised of the Harmonic algorithm H and the Improved Harmonic algorithm C, for the two-dimensional online bin packing problem and proved that the algorithm has an asymptotic competitive ratio of at most 2.66013. Since the best known online algorithm for one-dimensional bin packing is the Super Harmonic algorithm [Seiden 2002], a natural question to ask is: could a better upper bound be achieved by using the Super Harmonic algorithm instead of the Improved Harmonic algorithm? However, as mentioned in Seiden and van Stee [2003], the previous analysis framework does not work. In this article, we give a positive answer for this question. A new upper bound of 2.5545 is obtained for 2-dimensional online bin packing. The main idea is to develop new weighting functions for the Super Harmonic algorithm and propose new techniques to bound the total weight in a rectangular bin.