@inproceedings{6c537897878f45c1a19a32a977489328,
title = "A Column Generation Based Heuristic for a Temporal Bin Packing Problem",
abstract = "We introduce a new temporal bin packing problem that originated from cloud computing. We have a finite set of items. For each item, we know an arriving time, processing time, and two weights (CPU, RAM). Some items we call large. Each bin (server) has two capacities and is divided into two identical parts (left and right). A regular item can be placed in one of them. A large item is divided into two identical parts and placed in both parts of a bin. Our goal is to pack all items into the minimum number of bins. For this NP-hard problem, we design a heuristic that is based on column generation to get lower and upper bounds. Preliminary computational experiments for real test instances indicate a small gap between the bounds. The average relative error is at most 0.88% for one week planning horizon and about 50000 items. The average running time is 21 s for a personal computer.",
keywords = "Bin packing, Column generation, Knapsack problem, Virtual machine",
author = "Alexey Ratushnyi and Yury Kochetov",
note = "Funding Information: Acknowledgement. The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project no. 0314-2019-0014). Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 20th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2021 ; Conference date: 05-07-2021 Through 10-07-2021",
year = "2021",
doi = "10.1007/978-3-030-77876-7_7",
language = "English",
isbn = "9783030778750",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "96--110",
editor = "Panos Pardalos and Michael Khachay and Alexander Kazakov",
booktitle = "Mathematical Optimization Theory and Operations Research - 20th International Conference, MOTOR 2021, Proceedings",
address = "Germany",
}