There is no EPTAS for two-dimensional knapsack
In the d-dimensional ( vector) knapsack problem given is a set of items, each having a d-dimensional size vector and a profit, and a d-dimensional bin. The goal is to select a subset of the items of maximum total profit such that the sum of all vectors is bounded by the bin capacity in each dimensio...
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Published in | Information processing letters Vol. 110; no. 16; pp. 707 - 710 |
---|---|
Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Amsterdam
Elsevier B.V
31.07.2010
Elsevier Elsevier Sequoia S.A |
Subjects | |
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Abstract | In the
d-dimensional (
vector)
knapsack problem given is a set of items, each having a
d-dimensional size vector and a profit, and a
d-dimensional bin. The goal is to select a subset of the items of maximum total profit such that the sum of all vectors is bounded by the bin capacity in each dimension. It is well known that, unless
P
=
NP
, there is no
fully polynomial-time approximation scheme for
d-dimensional knapsack, already for
d
=
2
. The best known result is a
polynomial-time approximation scheme (
PTAS) due to Frieze and Clarke [A.M. Frieze, M. Clarke, Approximation algorithms for the
m-dimensional 0–1 knapsack problem: worst-case and probabilistic analyses, European J. Operat. Res. 15 (1) (1984) 100–109] for the case where
d
⩾
2
is some fixed constant. A fundamental open question is whether the problem admits an
efficient PTAS (
EPTAS).
In this paper we resolve this question by showing that there is no EPTAS for
d-dimensional knapsack, already for
d
=
2
, unless
W
[
1
]
=
FPT
. Furthermore, we show that unless all problems in SNP are solvable in sub-exponential time, there is no approximation scheme for two-dimensional knapsack whose running time is
f
(
1
/
ε
)
|
I
|
o
(
1
/
ε
)
, for any function
f. Together, the two results suggest that a significant improvement over the running time of the scheme of Frieze and Clarke is unlikely to exist. |
---|---|
AbstractList | In the d-dimensional (vector) knapsack problem given is a set of items, each having a d-dimensional size vector and a profit, and a d-dimensional bin. The goal is to select a subset of the items of maximum total profit such that the sum of all vectors is bounded by the bin capacity in each dimension. It is well known that, unless P=NP, there is no fully polynomial-time approximation scheme for d-dimensional knapsack, already for d=2. The best known result is a polynomial-time approximation scheme (PTAS) due to Frieze and Clarke [A.M. Frieze, M. Clarke, Approximation algorithms for the m-dimensional 0-1 knapsack problem: worst-case and probabilistic analyses, European J. Operat. Res. 15 (1) (1984) 100-109] for the case where d[greater-or-equal, slanted]2 is some fixed constant. A fundamental open question is whether the problem admits an efficient PTAS (EPTAS). In this paper we resolve this question by showing that there is no EPTAS for d-dimensional knapsack, already for d=2, unless W[1]=FPT. Furthermore, we show that unless all problems in SNP are solvable in sub-exponential time, there is no approximation scheme for two-dimensional knapsack whose running time is [MathML equation], for any function f. Together, the two results suggest that a significant improvement over the running time of the scheme of Frieze and Clarke is unlikely to exist. In the d-dimensional (vector) knapsack problem given is a set of items, each having a d-dimensional size vector and a profit, and a d-dimensional bin. The goal is to select a subset of the items of maximum total profit such that the sum of all vectors is bounded by the bin capacity in each dimension. It is well known that, unless P=NP, there is no fully polynomial-time approximation scheme for d-dimensional knapsack, already for d=2. The best known result is a polynomial-time approximation scheme (PTAS) due to Frieze and Clarke [A.M. Frieze, M. Clarke, Approximation algorithms for the m-dimensional 0-1 knapsack problem: worst-case and probabilistic analyses, European J. Operat. Res. 15 (1) (1984) 100-109] for the case where d≥2 is some fixed constant. A fundamental open question is whether the problem admits an efficient PTAS (EPTAS). In this paper the authors resolve this question by showing that there is no EPTAS for d-dimensional knapsack, already for d=2, unless W[1]=FPT. Furthermore, they show that unless all problems in SNP are solvable in sub-exponential time, there is no approximation scheme for two-dimensional knapsack whose running time is ..., for any function f. Together, the two results suggest that a significant improvement over the running time of the scheme of Frieze and Clarke is unlikely to exist. (ProQuest: ... denotes formulae/symbols omitted.) In the d-dimensional ( vector) knapsack problem given is a set of items, each having a d-dimensional size vector and a profit, and a d-dimensional bin. The goal is to select a subset of the items of maximum total profit such that the sum of all vectors is bounded by the bin capacity in each dimension. It is well known that, unless P = NP , there is no fully polynomial-time approximation scheme for d-dimensional knapsack, already for d = 2 . The best known result is a polynomial-time approximation scheme ( PTAS) due to Frieze and Clarke [A.M. Frieze, M. Clarke, Approximation algorithms for the m-dimensional 0–1 knapsack problem: worst-case and probabilistic analyses, European J. Operat. Res. 15 (1) (1984) 100–109] for the case where d ⩾ 2 is some fixed constant. A fundamental open question is whether the problem admits an efficient PTAS ( EPTAS). In this paper we resolve this question by showing that there is no EPTAS for d-dimensional knapsack, already for d = 2 , unless W [ 1 ] = FPT . Furthermore, we show that unless all problems in SNP are solvable in sub-exponential time, there is no approximation scheme for two-dimensional knapsack whose running time is f ( 1 / ε ) | I | o ( 1 / ε ) , for any function f. Together, the two results suggest that a significant improvement over the running time of the scheme of Frieze and Clarke is unlikely to exist. |
Author | Kulik, Ariel Shachnai, Hadas |
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Cites_doi | 10.1287/moor.9.2.244 10.1023/A:1009813105532 10.1016/S0377-2217(99)00261-1 10.1016/0304-3975(94)00097-3 10.1007/978-1-4612-0515-9 10.1145/1008861.1008867 10.1016/0377-2217(84)90053-5 10.1016/0022-0000(91)90023-X 10.1023/B:JOCO.0000021934.29833.6b |
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Keywords | Theory of computation Efficient polynomial-time approximation schemes Two-dimensional knapsack Parameterized complexity Computer theory Polynomial approximation Approximation algorithm Complexity Knapsack problem Polynomial time Maximum Information processing Two-dimensional calculations Vector Algorithm analysis |
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References | Jansen (bib009) 2009 Frieze, Clarke (bib006) 1984; 15 Caprara, Kellerer, Pferschy, Pisinger (bib001) 2000; 123 Chen, Huang, Kanj, Xia (bib002) 2004 Downey, Fellows (bib003) 1999 Vazirani (bib016) 2001 Magazine, Chern (bib014) 1984; 9 Kellerer, Pferschy, Pisinger (bib012) October 2004 Kellerer, Pferschy (bib011) 2004; 8 Kellerer, Pferschy (bib010) 1999; 3 Flum, Grohe (bib005) 2006 Gens, Levner (bib007) 1980; 12 Korte, Schrader (bib013) 1981; 4 Papadimitriou, Yannakakis (bib015) 1991; 43 Downey, Fellows (bib004) 1995; 141 (bib008) 1996 Kellerer (10.1016/j.ipl.2010.05.031_bib010) 1999; 3 Caprara (10.1016/j.ipl.2010.05.031_bib001) 2000; 123 Jansen (10.1016/j.ipl.2010.05.031_bib009) 2009 Kellerer (10.1016/j.ipl.2010.05.031_bib012) 2004 Downey (10.1016/j.ipl.2010.05.031_bib003) 1999 Flum (10.1016/j.ipl.2010.05.031_bib005) 2006 Kellerer (10.1016/j.ipl.2010.05.031_bib011) 2004; 8 Chen (10.1016/j.ipl.2010.05.031_bib002) 2004 Korte (10.1016/j.ipl.2010.05.031_bib013) 1981; 4 Vazirani (10.1016/j.ipl.2010.05.031_bib016) 2001 Magazine (10.1016/j.ipl.2010.05.031_bib014) 1984; 9 Papadimitriou (10.1016/j.ipl.2010.05.031_bib015) 1991; 43 Downey (10.1016/j.ipl.2010.05.031_bib004) 1995; 141 (10.1016/j.ipl.2010.05.031_bib008) 1996 Gens (10.1016/j.ipl.2010.05.031_bib007) 1980; 12 Frieze (10.1016/j.ipl.2010.05.031_bib006) 1984; 15 |
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Sci. doi: 10.1016/0304-3975(94)00097-3 contributor: fullname: Downey – year: 2006 ident: 10.1016/j.ipl.2010.05.031_bib005 article-title: Parameterized Complexity Theory contributor: fullname: Flum – volume: 4 start-page: 415 year: 1981 ident: 10.1016/j.ipl.2010.05.031_bib013 article-title: On the existence of fast approximation schemes publication-title: Nonlinear Programming contributor: fullname: Korte – year: 1999 ident: 10.1016/j.ipl.2010.05.031_bib003 article-title: Parameterized Complexity doi: 10.1007/978-1-4612-0515-9 contributor: fullname: Downey – volume: 12 start-page: 52 issue: 3 year: 1980 ident: 10.1016/j.ipl.2010.05.031_bib007 article-title: Complexity of approximation algorithms for combinatorial problems: a survey publication-title: SIGACT News doi: 10.1145/1008861.1008867 contributor: fullname: Gens – volume: 15 start-page: 100 issue: 1 year: 1984 ident: 10.1016/j.ipl.2010.05.031_bib006 article-title: Approximation algorithms for the m-dimensional 0–1 knapsack problem: worst-case and probabilistic analyses publication-title: European J. 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Optim. doi: 10.1023/B:JOCO.0000021934.29833.6b contributor: fullname: Kellerer – start-page: 665 year: 2009 ident: 10.1016/j.ipl.2010.05.031_bib009 article-title: Parameterized approximation scheme for the multiple knapsack problem contributor: fullname: Jansen – year: 1996 ident: 10.1016/j.ipl.2010.05.031_bib008 |
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Snippet | In the
d-dimensional (
vector)
knapsack problem given is a set of items, each having a
d-dimensional size vector and a profit, and a
d-dimensional bin. The... In the d-dimensional (vector) knapsack problem given is a set of items, each having a d-dimensional size vector and a profit, and a d-dimensional bin. The goal... |
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SubjectTerms | Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Approximation Approximations and expansions Computer science; control theory; systems Efficient polynomial-time approximation schemes Exact sciences and technology Knapsack problem Mail order Mathematical analysis Mathematics Miscellaneous Parameterized complexity Probabilistic analysis Problem solving Running Sciences and techniques of general use Studies Theoretical computing Theory of computation Two dimensional Two-dimensional knapsack Vectors (mathematics) |
Title | There is no EPTAS for two-dimensional knapsack |
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