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140122 ||| eng |
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|a 9781475727876
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|a Cela, E.
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|a The Quadratic Assignment Problem
|h Elektronische Ressource
|b Theory and Algorithms
|c by E. Cela
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| 250 |
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|a 1st ed. 1998
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| 260 |
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|a New York, NY
|b Springer US
|c 1998, 1998
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| 300 |
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|a XV, 287 p
|b online resource
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|a 1 Problem Statement and Complexity Aspects -- 2 Exact Algorithms and Lower Bounds -- 3 Heuristics and Asymptotic Behavior -- 4 QAPS on Specially Structured Matrices -- 5 Two More Restricted Versions of the QAP -- 6 QAPS Arising as Optimization Problems in Graphs -- 7 On the Biquadratic Assignment Problem (BIQAP) -- References -- Notation Index
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| 653 |
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|a Optimization
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|a Computer science
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|a Computer science / Mathematics
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|a Discrete Mathematics in Computer Science
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| 653 |
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|a Algorithms
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| 653 |
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|a Discrete Mathematics
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| 653 |
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|a Discrete mathematics
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|a Theory of Computation
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| 653 |
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|a Mathematical optimization
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|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
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|a Combinatorial Optimization
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| 028 |
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|a 10.1007/978-1-4757-2787-6
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| 856 |
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|u https://doi.org/10.1007/978-1-4757-2787-6?nosfx=y
|x Verlag
|3 Volltext
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|a 519.6
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|a The quadratic assignment problem (QAP) was introduced in 1957 by Koopmans and Beckmann to model a plant location problem. Since then the QAP has been object of numerous investigations by mathematicians, computers scientists, ope- tions researchers and practitioners. Nowadays the QAP is widely considered as a classical combinatorial optimization problem which is (still) attractive from many points of view. In our opinion there are at last three main reasons which make the QAP a popular problem in combinatorial optimization. First, the number of re- life problems which are mathematically modeled by QAPs has been continuously increasing and the variety of the fields they belong to is astonishing. To recall just a restricted number among the applications of the QAP let us mention placement problems, scheduling, manufacturing, VLSI design, statistical data analysis, and parallel and distributed computing. Secondly, a number of other well known c- binatorial optimization problems can be formulated as QAPs. Typical examples are the traveling salesman problem and a large number of optimization problems in graphs such as the maximum clique problem, the graph partitioning problem and the minimum feedback arc set problem. Finally, from a computational point of view the QAP is a very difficult problem. The QAP is not only NP-hard and - hard to approximate, but it is also practically intractable: it is generally considered as impossible to solve (to optimality) QAP instances of size larger than 20 within reasonable time limits
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