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Approximation Algorithms || Bin Packing

✍ Scribed by Vazirani, Vijay V.


Book ID
120247091
Publisher
Springer Berlin Heidelberg
Year
2003
Tongue
English
Weight
598 KB
Edition
9
Category
Article
ISBN
3662045656

No coin nor oath required. For personal study only.

✦ Synopsis


Although this may seem a paradox, all exact science is dominated by the idea of approximation. Bertrand Russell (1872-1970) Most natural optimization problems, including those arising in important application areas, are NP-hard. Therefore, under the widely believed conΒ­ jecture that P -=/= NP, their exact solution is prohibitively time consuming. Charting the landscape of approximability of these problems, via polynomial time algorithms, therefore becomes a compelling subject of scientific inquiry in computer science and mathematics. This book presents the theory of apΒ­ proximation algorithms as it stands today. It is reasonable to expect the picture to change with time. This book is divided into three parts. In Part I we cover combinatoΒ­ rial algorithms for a number of important problems, using a wide variety of algorithm design techniques. The latter may give Part I a non-cohesive appearance. However, this is to be expected - nature is very rich, and we cannot expect a few tricks to help solve the diverse collection of NP-hard problems. Indeed, in this part, we have purposely refrained from tightly catΒ­ egorizing algorithmic techniques so as not to trivialize matters. Instead, we have attempted to capture, as accurately as possible, the individual character of each problem, and point out connections between problems and algorithms for solving them.


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A 1312 approximation algorithm for bin p
✍ Paolo Dell'Olmo; Hans Kellerer; Maria Grazia Speranza; Zsolt Tuza πŸ“‚ Article πŸ“… 1998 πŸ› Elsevier Science 🌐 English βš– 430 KB

A set of items has to be assigned to a set of bins with size one. If necessary, the size of the bins can be extended. The objective is to minimize the total size, i.e., the sum of the sizes of the bins. The Longest Processing Time heuristic is applied to this NP-hard problem. For this approximation