Intrinsic complexity estimates in polynomial optimization

被引:18
作者
Bank, Bernd [1 ]
Giusti, Marc [2 ]
Heintz, Joos [3 ,4 ,5 ]
El Din, Mohab Safey [6 ,7 ,8 ]
机构
[1] Humboldt Univ, Inst Math, D-10099 Berlin, Germany
[2] Ecole Polytech, CNRS, Lab LIX, F-91228 Palaiseau, France
[3] Univ Buenos Aires, Dept Comp, RA-1428 Buenos Aires, DF, Argentina
[4] Consejo Nacl Invest Cient & Tecn, RA-1428 Buenos Aires, DF, Argentina
[5] Univ Cantabria, Fac Ciencias, Dept Matemat Estat & Comp, Santander 39071, Spain
[6] Univ Paris 06, Univ Sorbonne, F-75252 Paris 05, France
[7] INRIA Paris Rocquencourt, POLSYS Project, Paris, France
[8] Inst Univ France, UMR 7606, CNRS, LIP6, Paris, France
关键词
Polynomial optimization; Intrinsic complexity; Degree of varieties; GENERALIZED POLAR VARIETIES; ELIMINATION; COMPUTATION; GEOMETRY; SETS;
D O I
10.1016/j.jco.2014.02.005
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
It is known that point searching in basic semialgebraic sets and the search for globally minimal points in polynomial optimization tasks can be carried out using (s d)(O(n)) arithmetic operations, where n and s are the numbers of variables and constraints and d is the maximal degree of the polynomials involved. Subject to certain conditions, we associate to each of these problems an intrinsic system degree which becomes in worst case of order (n d)(O(n)) and which measures the intrinsic complexity of the task under consideration. We design non-uniform deterministic or uniform probabilistic algorithms of intrinsic, quasi-polynomial complexity which solve these problems. (C) 2014 Elsevier Inc. All rights reserved.
引用
收藏
页码:430 / 443
页数:14
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