Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
The steiner problem with edge lengths 1 and 2,
Information Processing Letters
Fixed-parameter tractability and completeness II: on completeness for W[1]
Theoretical Computer Science
Performance Guarantees for Approximation Algorithms Depending on Parametrized Triangle Inequalities
SIAM Journal on Discrete Mathematics
Fixed-Parameter Tractability and Completeness I: Basic Results
SIAM Journal on Computing
The hardness of approximation: gap location
Computational Complexity
On the efficiency of polynomial time approximation schemes
Information Processing Letters
Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems
Journal of the ACM (JACM)
P-Complete Approximation Problems
Journal of the ACM (JACM)
Performance guarantees for the TSP with a parameterized triangle inequality
Information Processing Letters
Approximation algorithms
Complexity and Approximation: Combinatorial Optimization Problems and Their Approximability Properties
Algorithmics for Hard Problems
Algorithmics for Hard Problems
CIAC '00 Proceedings of the 4th Italian Conference on Algorithms and Complexity
Bidimensionality: new connections between FPT algorithms and PTASs
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Confronting hardness using a hybrid approach
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity Theory (Texts in Theoretical Computer Science. An EATCS Series)
Parameterized Complexity of Vertex Cover Variants
Theory of Computing Systems
The Parameterized Approximability of TSP with Deadlines
Theory of Computing Systems
Parameterized approximation of dominating set problems
Information Processing Letters
Reoptimization of Steiner trees: Changing the terminal set
Theoretical Computer Science
Hierarchies of memory limited computations
FOCS '65 Proceedings of the 6th Annual Symposium on Switching Circuit Theory and Logical Design (SWCT 1965)
On the hardness of reoptimization
SOFSEM'08 Proceedings of the 34th conference on Current trends in theory and practice of computer science
Paired approximation problems and incompatible inapproximabilities
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
SIAM Journal on Discrete Mathematics
On parameterized approximability
IWPEC'06 Proceedings of the Second international conference on Parameterized and Exact Computation
Parameterized approximation problems
IWPEC'06 Proceedings of the Second international conference on Parameterized and Exact Computation
Improved approximations for TSP with simple precedence constraints
CIAC'10 Proceedings of the 7th international conference on Algorithms and Complexity
Parameterized Complexity and Approximation Algorithms
The Computer Journal
The Bidimensionality Theory and Its Algorithmic Applications 1
The Computer Journal
| Hi-index | 0.00 |
Under the usual complexity-theoretic assumptions like P ≠ NP, many practically relevant optimization problems are provably hard to solve or even to approximate. But most of these hardness results are derived for worst-case scenarios, and it is in many cases not clear whether the actual problem instances arising in practical applications exhibit this worst-case behaviour. Thus, a recent branch of algorithmic research aims at a more fine-grained analysis of the hardness of optimization problems. The main idea behind this analysis is to find some parameter according to which one can classify the hardness of problem instances. This approach does not only lead to new hardness results, but can also be used to design improved approximation algorithms for practically relevant subclasses of problem instances. In this paper, we survey several different approaches for such improved approximation results achieved by a fine-grained classification of problem instances.