Knapsack Approximation is a computational method in the field of approximation algorithms that systematically derives near-optimal solutions to the knapsack problem by relaxing or simplifying the original constraints while guaranteeing a performance ratio relative to the optimal solution.
503
Publications
36.9K
Citations
1K
Authors
512
Institutions
Publications per year
2017–2026
110
Publications
503
1–5 of 503
Authors
1K
- UP
11
h-index
- DP
10
h-index
- SM
8
h-index
- HK
6
h-index
- PT
6
h-index
1–5 of 1K
Institutions
512
University of Graz
Graz, Austria
14 h-index
20 publications
1.1K citations
University of Bologna
Bologna, Italy
14 h-index
25 publications
8.8K citations
Centre National de la Recherche Scientifique
Paris, France
13 h-index
25 publications
1.1K citations
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
18 publications
1.1K citations
Hebei GEO University
Shijiazhuang, China
9 h-index
24 publications
1.1K citations
University of Copenhagen
Copenhagen, Denmark
9 h-index
9 publications
1.3K citations
University of Maryland, College Park
College Park, United States
8 h-index
12 publications
245 citations
Carnegie Mellon University
Pittsburgh, United States
8 h-index
20 publications
1.5K citations
1–8 of 512
Venues
- European Journal of Operational Research
43 publications · 4.7K citations
26
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- Computers & Operations Research
24 publications · 1.3K citations
20
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- Operations Research Letters
23 publications · 1.7K citations
18
h-index
- Mathematical Programming
16 publications · 1K citations
13
h-index
- Discrete Applied Mathematics
14 publications · 642 citations
13
h-index
1–5