Nearly linear-time packing and covering LP solvers: Achieving width-independence and -convergence
Packing and covering linear programs (PC-LP s) form an important class of linear programs (LPs) across computer science, operations research, and optimization. Luby and Nisan (in: STOC, ACM Press, New York, 1993 ) constructed an iterative algorithm for approximately solving PC-LP s in nearly linear...
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Veröffentlicht in: | Mathematical programming 2019-05, Vol.175 (1-2), p.307-353 |
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Zusammenfassung: | Packing and covering linear programs (PC-LP s) form an important class of linear programs (LPs) across computer science, operations research, and optimization. Luby and Nisan (in: STOC, ACM Press, New York,
1993
) constructed an iterative algorithm for approximately solving PC-LP s in
nearly linear time
, where the time complexity scales nearly linearly in
N
, the number of nonzero entries of the matrix, and polynomially in
ε
, the (multiplicative) approximation error. Unfortunately, existing nearly linear-time algorithms (Plotkin et al. in Math Oper Res 20(2):257–301,
1995
; Bartal et al., in: Proceedings 38th annual symposium on foundations of computer science, IEEE Computer Society,
1997
; Young, in: 42nd annual IEEE symposium on foundations of computer science (FOCS’01), IEEE Computer Society,
2001
; Koufogiannakis and Young in Algorithmica 70:494–506,
2013
; Young in Nearly linear-time approximation schemes for mixed packing/covering and facility-location linear programs,
2014
.
arXiv:1407.3015
; Allen-Zhu and Orecchia, in: SODA,
2015
) for solving PC-LP s require time at least proportional to
ε
-
2
. In this paper, we break this longstanding barrier by designing a packing solver that runs in time
O
~
(
N
ε
-
1
)
and covering LP solver that runs in time
O
~
(
N
ε
-
1.5
)
. Our packing solver can be extended to run in time
O
~
(
N
ε
-
1
)
for a class of well-behaved covering programs. In a follow-up work, Wang et al. (in: ICALP,
2016
) showed that all covering LPs can be converted into well-behaved ones by a reduction that blows up the problem size only logarithmically. |
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ISSN: | 0025-5610 1436-4646 |
DOI: | 10.1007/s10107-018-1244-x |