DocumentCode :
2362643
Title :
Towards average-case complexity analysis of NP optimization problems
Author :
Schuler, Rainer ; Watanabe, Osamu
Author_Institution :
Abteilung Theor. Inf., Ulm Univ., Germany
fYear :
1995
fDate :
19-22 Jun 1995
Firstpage :
148
Lastpage :
159
Abstract :
For the worst-case complexity measure, if P=NP, then P=OptP, i.e., all NP optimization problems are polynomial-time solvable. On the other hand, it is not clear whether a similar relation holds when considering average-case complexity. We investigate the relationship between the complexity of NP decision problems and that of NP optimization problems under polynomial-time computable distributions, and study what makes them (seemingly) different. It is shown that the difference between P ttNP-samplable and PNP-samplable distributions is crucial
Keywords :
computational complexity; decision theory; optimisation; NP decision problems; NP optimization problems; average-case complexity analysis; polynomial-time computable distributions; samplable distributions; worst-case complexity measure; Complexity theory; Computer science; Cost function; Distributed computing; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Structure in Complexity Theory Conference, 1995., Proceedings of Tenth Annual IEEE
Conference_Location :
Minneapolis, MN
ISSN :
1063-6870
Print_ISBN :
0-8186-7052-5
Type :
conf
DOI :
10.1109/SCT.1995.514854
Filename :
514854
Link To Document :
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