Fast algorithms for bin packing
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Low-order polynomial time algorithms for near-optimal solutions to the problem of bin packing are studied and linear-time approximations to these packing rules whose worst case behavior is as good as that of FIRST FIT under a large variety of restrictions on the input are presented.About:
This article is published in Journal of Computer and System Sciences.The article was published on 1974-06-01 and is currently open access. It has received 539 citations till now. The article focuses on the topics: Square packing in a square & Set packing.read more
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Book ChapterDOI
Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey
TL;DR: In this article, the authors survey the state of the art with respect to optimization and approximation algorithms and interpret these in terms of computational complexity theory, and indicate some problems for future research and include a selective bibliography.
Journal ArticleDOI
Some simplified NP-complete graph problems
TL;DR: This paper shows that a number of NP - complete problems remain NP -complete even when their domains are substantially restricted, and determines essentially the lowest possible upper bounds on node degree for which the problems remainNP -complete.
Journal ArticleDOI
Worst-Case Performance Bounds for Simple One-Dimensional Packing Algorithms
TL;DR: This work examines the performance of a number of simple algorithms which obtain “good” placements and shows that neither the first-fit nor the best-fit algorithm will ever use more than $\frac{17}{10}L^ * + 2$ bins.
Journal ArticleDOI
The NP-completeness column: An ongoing guide
TL;DR: This is the fourteenth edition of a quarterly column that provides continuing coverage of new developments in the theory of NP-completeness, and readers who have results they would like mentioned (NP-hardness, PSPACE- hardness, polynomialtime-solvability, etc.), or open problems they wouldlike publicized, should send them to David S. Johnson.
Journal ArticleDOI
Bin packing can be solved within 1 + ε in linear time
TL;DR: In this paper, it was shown that for any positive e, there exists an O(n)-time algorithmS such that, if S(L) denotes the number of bins used by S for L, thenS(L)/L*≦1+e for anyL provided L* is sufficiently large.
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Reducibility Among Combinatorial Problems.
TL;DR: Throughout the 1960s I worked on combinatorial optimization problems including logic circuit design with Paul Roth and assembly line balancing and the traveling salesman problem with Mike Held, which made me aware of the importance of distinction between polynomial-time and superpolynomial-time solvability.
Proceedings ArticleDOI
The complexity of theorem-proving procedures
TL;DR: It is shown that any recognition problem solved by a polynomial time-bounded nondeterministic Turing machine can be “reduced” to the problem of determining whether a given propositional formula is a tautology.
Journal ArticleDOI
Approximation algorithms for combinatorial problems
TL;DR: For the problem of finding the maximum clique in a graph, no algorithm has been found for which the ratio does not grow at least as fast as n^@e, where n is the problem size and @e>0 depends on the algorithm.
An algorithm for the organization of information
TL;DR: The organization of information placed in the points of an automatic computer is discussed and the role of memory, storage and retrieval in this regard is discussed.