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Pivot versus interior point methods:: Pros and cons
被引:38
|作者:
Illés, T
Terlaky, T
机构:
[1] McMaster Univ, Dept Comp & Software, Hamilton, ON L8S 4L7, Canada
[2] Eotvos Lorand Univ, Dept Operat Res, Budapest, Hungary
关键词:
linear programming;
linear optimization;
pivot methods;
simplex algorithms;
interior point methods;
complexity;
sensitivity analysis;
D O I:
10.1016/S0377-2217(02)00061-9
中图分类号:
C93 [管理学];
学科分类号:
12 ;
1201 ;
1202 ;
120202 ;
摘要:
Linear optimization (LO) is the fundamental problem of mathematical optimization. It admits an enormous number of applications in economics, engineering, science and many other fields. The three most significant classes of algorithms for solving LO problems are: pivot, ellipsoid and interior point methods. Because ellipsoid methods are not efficient in practice we will concentrate on the computationally successful simplex and primal-dual interior point methods only. and summarize the pros and cons of these algorithm classes. (C) 2002 Elsevier Science B.V. All rights reserved.
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页码:170 / 190
页数:21
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