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Journal ArticleDOI

Pipeline architectures for dynamic programming algorithms

TLDR
This paper presents pipeline architectures for the dynamic programming algorithms for the knapsack problems that enable us to achieve an optimal speedup using processor arrays, queues, and memory modules.
Abstract
Dynamic programming is one of the most powerful approaches to many combinatorial optimization problems. In this paper, we present pipeline architectures for the dynamic programming algorithms for the knapsack problems. They enable us to achieve an optimal speedup using processor arrays, queues, and memory modules. The processor arrays can be regarded as pipelines where the dynamic programming algorithms are implemented through pipelining.

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Citations
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Journal ArticleDOI

Exact algorithms for the guillotine strip cutting/packing problem

TL;DR: The proposed exact algorithms are able to solve some small and medium problem instances within reasonable execution times and are easily parallelizable and this is one of their important futures.
Posted Content

Exact Algorithms for Large-Scale Unconstrained Two and Three Staged Cutting Problems

TL;DR: In this paper, exact algorithms for solving both two-and three-staged unconstrained (un) weighted cutting problems were proposed, and the performance of the exact algorithms were evaluated on some problem instances of the literature and other hard randomly-generated problem instances.
Journal ArticleDOI

Exact Algorithms for Large-Scale Unconstrained Two and Three Staged Cutting Problems

TL;DR: Two exact algorithms for solving both two-staged and three staged unconstrained (un)weighted cutting problems and their performance is evaluated on some problem instances of the literature and other hard randomly-generated problem instances.
Journal ArticleDOI

The DH/KD algorithm: a hybrid approach for unconstrained two-dimensional cutting problems

TL;DR: A hybrid approach which combines two heuristics from the literature is developed, which can be seen as a generalization of the two heuristic and solves large problem instances very well within small computational time.
Journal ArticleDOI

Load balancing methods and parallel dynamic programming algorithm using dominance technique applied to the 0--1 knapsack problem

TL;DR: This is the first time for which computational experiments on a supercomputer are presented for a parallel dynamic programming algorithm using dominance technique and processor cooperation for the 0-1 knapsack problem.
References
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Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Book

Dynamic Programming

TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
Book

Integer programming

TL;DR: The principles of integer programming are directed toward finding solutions to problems from the fields of economic planning, engineering design, and combinatorial optimization as mentioned in this paper, which is a standard of graduate-level courses since 1972.
Book

Computer Architecture and Parallel Processing

Kai Hwang, +1 more
TL;DR: The authors have divided the use of computers into the following four levels of sophistication: data processing, information processing, knowledge processing, and intelligence processing.
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