Sensitivity analysis for minimum Hamiltonian path and traveling salesman problems
ARIDAM III Selected papers on Third advanced research institute of discrete applied mathematics
Some concepts of stability analysis in combinatorial optimization
Proceedings of the workshop on Discrete algorithms
Advances in computational and stochastic optimization, logic programming, and heuristic search
Stability aspects of the traveling salesman problem based on k-best solutions
Discrete Applied Mathematics
On the complexity of postoptimality analysis of 0/1 programs
Discrete Applied Mathematics
Algorithmics for hard problems: introduction to combinatorial optimization, randomization, approximation, and heuristics
The vehicle routing problem
The Parameterized Approximability of TSP with Deadlines
Theory of Computing Systems
On the approximation hardness of some generalizations of TSP
SWAT'06 Proceedings of the 10th Scandinavian conference on Algorithm Theory
Reoptimization of the metric deadline TSP
Journal of Discrete Algorithms
| Hi-index | 5.23 |
Given an instance of an optimization problem together with an optimal solution, we consider the scenario in which this instance is modified locally. In graph problems, e.g., a singular edge might be removed or added, or an edge weight might be varied, etc. For a problem U and such a local modification operation, let lm-U (local-modification-U) denote the resulting problem. The question is whether it is possible to exploit the additional knowledge of an optimal solution to the original instance or not, i.e.,whether lm-U is computationally more tractable than U. While positive examples are known e.g. for metric TSP, we give some negative examples here: Metric TSP with deadlines (time windows), if a single deadline or the cost of a single edge is modified, exhibits the same lower bounds on the approximability in these local-modification versions as those currently known for the original problem.