@inproceedings{b8500dae166a43c690c717eeaa68672f,
title = "An improved online multidimensional bin packing Algorithm",
abstract = "As a fundamental optimization problem, the problem of packing a given set of objects into the fewest possible bins has both important theoretical significance in algorithms and operations research and great application values for resource allocation, particularly in cloud computing and data center management. In this paper we address the multidimensional online bin packing problem and present an algorithm based on the ROUNDdM algorithm proposed by Csirik & Van Vliet [6]. The ROUNDdM algorithm is a generalisation of the harmonic partitioning scheme in [7], and guarantees a worst case approximation ratio of 1.691d for d-dimensions and an average case ratio of 1.2899d. Our HYBRID-ROUNDdM algorithm uses a harmonic based hybrid partitioning scheme and improves this average case approximation ratio to 1.0797d while guaranteeing the same worst case approximation ratio.",
keywords = "Approximation algorithm, Bin packing, Optimization",
author = "Vincent Portella and Hong Shen",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019 ; Conference date: 05-12-2019 Through 07-12-2019",
year = "2019",
month = dec,
doi = "10.1109/PDCAT46702.2019.00094",
language = "English",
series = "Proceedings - 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "479--482",
editor = "Hui Tian and Hong Shen and Tan, {Wee Lum}",
booktitle = "Proceedings - 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019",
address = "United States",
}