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＜電子ブック＞
The Quadratic Assignment Problem : Theory and Algorithms / by E. Cela
(Combinatorial Optimization ; 1)

版	1st ed. 1998.
出版者	(New York, NY : Springer US : Imprint: Springer)
出版年	1998
本文言語	英語
大きさ	XV, 287 p : online resource
著者標目	*Cela, E author SpringerLink (Online service)
件　名	LCSH:Mathematical optimization LCSH:Algorithms LCSH:Computer science LCSH:Computer science -- Mathematics  全ての件名で検索 LCSH:Discrete mathematics FREE:Optimization FREE:Algorithms FREE:Theory of Computation FREE:Discrete Mathematics in Computer Science FREE:Discrete Mathematics
一般注記	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 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 HTTP:URL=https://doi.org/10.1007/978-1-4757-2787-6

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