Fibonacci heaps and their uses in improved network optimization algorithms
Journal of the ACM (JACM)
An approximation algorithm for the general routing problem
Information Processing Letters
Scheduling with forbidden sets
Discrete Applied Mathematics - Special issue on models and algorithms for planning and scheduling problems
Approximation Algorithms for Some Postman Problems
Journal of the ACM (JACM)
Simultaneous disruption recovery of a train timetable and crew roster in real time
Computers and Operations Research
Reoptimization of minimum and maximum traveling salesman's tours
Journal of Discrete Algorithms
Disruption management in the airline industry-Concepts, models and methods
Computers and Operations Research
Reoptimization of the metric deadline TSP
Journal of Discrete Algorithms
On the hardness of reoptimization
SOFSEM'08 Proceedings of the 34th conference on Current trends in theory and practice of computer science
Fast reoptimization for the minimum spanning tree problem
Journal of Discrete Algorithms
Reoptimizing the 0-1 knapsack problem
Discrete Applied Mathematics
Reoptimization of set covering problems
Cybernetics and Systems Analysis
Checking the Feasibility of Dial-a-Ride Instances Using Constraint Programming
Transportation Science
A new algorithm for reoptimizing shortest paths when the arc costs change
Operations Research Letters
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Given an instance of the Rural Postman Problem (RPP) together with its optimal solution, we study the problem of finding a good feasible solution after a perturbation of the instance has occurred. We refer to this problem as the reoptimization of the RPP. We first consider the case where a new required edge is added. Second, we address the case where an edge (required or not) is removed. We show that the reoptimization problems are NP-hard. We consider a heuristic for the case where a new required edge is added which is a modification of the cheapest insertion algorithm for the traveling salesman problem and show that it has a worst-case ratio equal to 2. Moreover, we show that simple algorithms to remove an edge from an optimal RPP tour guarantee a tight ratio equal to 3/2. Computational tests are made to compare the performance of these algorithms with respect to the Frederickson algorithm running from scratch.