An efficient fully polynomial approximation scheme for the Subset-Sum Problem
Given a set of n positive integers and a knapsack of capacity c, the Subset-Sum Problem is to find a subset the sum of which is closest to c without exceeding the value c. In this paper we present a fully polynomial approximation scheme which solves the Subset-Sum Problem with accuracy ε in time O(...
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          | Published in | Journal of computer and system sciences Vol. 66; no. 2; pp. 349 - 370 | 
|---|---|
| Main Authors | , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
            Elsevier Inc
    
        01.03.2003
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 0022-0000 1090-2724  | 
| DOI | 10.1016/S0022-0000(03)00006-0 | 
Cover
| Abstract | Given a set of
n positive integers and a knapsack of capacity
c, the Subset-Sum Problem is to find a subset the sum of which is closest to
c without exceeding the value
c. In this paper we present a fully polynomial approximation scheme which solves the Subset-Sum Problem with accuracy
ε in time
O(
min{n·1/ε,n+1/ε
2
log(1/ε)})
and space
O(
n+1/
ε). This scheme has a better time and space complexity than previously known approximation schemes. Moreover, the scheme always finds the optimal solution if it is smaller than (1−
ε)
c. Computational results show that the scheme efficiently solves instances with up to 5000 items with a guaranteed relative error smaller than 1/1000. | 
    
|---|---|
| AbstractList | Given a set of
n positive integers and a knapsack of capacity
c, the Subset-Sum Problem is to find a subset the sum of which is closest to
c without exceeding the value
c. In this paper we present a fully polynomial approximation scheme which solves the Subset-Sum Problem with accuracy
ε in time
O(
min{n·1/ε,n+1/ε
2
log(1/ε)})
and space
O(
n+1/
ε). This scheme has a better time and space complexity than previously known approximation schemes. Moreover, the scheme always finds the optimal solution if it is smaller than (1−
ε)
c. Computational results show that the scheme efficiently solves instances with up to 5000 items with a guaranteed relative error smaller than 1/1000. | 
    
| Author | Mansini, Renata Speranza, Maria Grazia Kellerer, Hans Pferschy, Ulrich  | 
    
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| Keywords | Fully polynomial approximation scheme Subset-sum problem Worst-case performance Knapsack problem  | 
    
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| Snippet | Given a set of
n positive integers and a knapsack of capacity
c, the Subset-Sum Problem is to find a subset the sum of which is closest to
c without exceeding... | 
    
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| SubjectTerms | Fully polynomial approximation scheme Knapsack problem Subset-sum problem Worst-case performance  | 
    
| Title | An efficient fully polynomial approximation scheme for the Subset-Sum Problem | 
    
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