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| Content Provider | Society for Industrial and Applied Mathematics (SIAM) |
|---|---|
| Author | Jansen, Klaus |
| Copyright Year | 2009 |
| Abstract | The multiple knapsack problem (MKP) is a well-known generalization of the classical knapsack problem. We are given a set A of n items and set B of m bins (knapsacks) such that each item $a \in A$ has a size $size(a)$ and a profit value $profit(a)$, and each bin $b \in B$ has a capacity $c(b)$. The goal is to find a subset $U \subset A$ of maximum total profit such that U can be packed into B without exceeding the capacities. The decision version of MKP is strongly NP-complete, since it is a generalization of the classical knapsack and bin packing problem. Furthermore, MKP does not admit a fully time polynomial time approximation scheme (FPTAS) even if the number m of bins is two. Kellerer gave a polynomial time approximation scheme (PTAS) for MKP with identical capacities and Chekuri and Khanna presented a PTAS for MKP with general capacities with running time $n^{O(\log(1/\epsilon)/\epsilon^8)}$. In this paper we propose an efficient PTAS (EPTAS) with parameterized running time $2^{O(\log(1/\epsilon)/\epsilon^5)} \cdot poly(n) + O(m)$ for MKP. This also solves an open question by Chekuri and Khanna. |
| Starting Page | 1392 |
| Ending Page | 1412 |
| Page Count | 21 |
| File Format | |
| ISSN | 00975397 |
| DOI | 10.1137/080731207 |
| e-ISSN | 10957111 |
| Journal | SIAM Journal on Computing (SMJCAT) |
| Issue Number | 4 |
| Volume Number | 39 |
| Language | English |
| Publisher | Society for Industrial and Applied Mathematics |
| Publisher Date | 2009-10-16 |
| Access Restriction | Subscribed |
| Subject Keyword | knapsack problem parameterized complexity Approximation algorithms Linear programming approximation algorithms Combinatorics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Mathematics Computer Science |
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