Scheduling project networks with resource constraints and time windows
Annals of Operations Research
The traveling salesman problem with distances one and two
Mathematics of Operations Research
Scheduling with forbidden sets
Discrete Applied Mathematics - Special issue on models and algorithms for planning and scheduling problems
Sparsification—a technique for speeding up dynamic graph algorithms
Journal of the ACM (JACM)
P-Complete Approximation Problems
Journal of the ACM (JACM)
A 7/8-approximation algorithm for metric Max TSP
Information Processing Letters
Maintaining Minimum Spanning Trees in Dynamic Graphs
ICALP '97 Proceedings of the 24th International Colloquium on Automata, Languages and Programming
Reoptimization of Steiner Trees
SWAT '08 Proceedings of the 11th Scandinavian workshop on Algorithm Theory
Improved deterministic approximation algorithms for Max TSP
Information Processing Letters
A theory and algorithms for combinatorial reoptimization
LATIN'12 Proceedings of the 10th Latin American international conference on Theoretical Informatics
Scheduling with multi-attribute setup times
Computers and Industrial Engineering
Reoptimization of the minimum total flow-time scheduling problem
MedAlg'12 Proceedings of the First Mediterranean conference on Design and Analysis of Algorithms
Reoptimizing the rural postman problem
Computers and Operations Research
Reallocation problems in scheduling
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
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In this paper, reoptimization versions of the traveling salesman problem (TSP) are addressed. Assume that an optimum solution of an instance is given and the goal is to determine if one can maintain a good solution when the instance is subject to minor modifications. We study the case where nodes are inserted in, or deleted from, the graph. When inserting a node, we show that the reoptimization problem for MinTSP is approximable within ratio 4/3 if the distance matrix is metric. We show that, dealing with metric MaxTSP, a simple heuristic is asymptotically optimum when a constant number of nodes are inserted. In the general case, we propose a 4/5-approximation algorithm for the reoptimization version of MaxTSP.