Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/147655 
Authors: 
Year of Publication: 
2005
Series/Report no.: 
Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel No. 597
Publisher: 
Universität Kiel, Institut für Betriebswirtschaftslehre, Kiel
Abstract: 
This paper addresses the robust shortest path problem with interval data, i.e. the case of classical shortest path problem with given source and sink when arc weights are not fixed but take their values from some intervals associated with arcs. The problem consists in finding a shortest path that minimizes so called robust deviation, i.e. deviation from an optimal solution under the worst case realization of interval weights. As it was proven in [9], the problem is NP-hard, therefore it is of great interest to tackle it with some metaheuristic approach, namely simulated annealing, in order to calculate an approximate solution for the large scale instances efficiently. We describe theoretical aspects and present the results of computational experiments. To the best of our knowledge, this is the first attempt to develop metaheuristic approach for solving the robust shortest path problem.
Subjects: 
shortest path problem
simulated annealing
uncertainty
robustness
Document Type: 
Working Paper
Document Version: 
Digitized Version

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