Maximum shortest path interdiction problem by upgrading edges on trees under weighted $$l_1$$ l 1 norm
Qiao Zhang,
Xiucui Guan () and
Panos M. Pardalos
Additional contact information
Qiao Zhang: Southeast University
Xiucui Guan: Southeast University
Panos M. Pardalos: University of Florida
Journal of Global Optimization, 2021, vol. 79, issue 4, No 9, 959-987
Abstract:
Abstract Network interdiction problems by deleting critical edges have wide applicatio ns. However, in some practical applications, the goal of deleting edges is difficult to achieve. We consider the maximum shortest path interdiction problem by upgrading edges on trees (MSPIT) under unit/weighted $$l_1$$ l 1 norm. We aim to maximize the the length of the shortest path from the root to all the leaves by increasing the weights of some edges such that the upgrade cost under unit/weighted $$l_1$$ l 1 norm is upper-bounded by a given value. We construct their mathematical models and prove some properties. We propose a revised algorithm for the problem (MSPIT) under unit $$l_1$$ l 1 norm with time complexity O(n), where n is the number of vertices in the tree. We put forward a primal dual algorithm in $$O(n^2)$$ O ( n 2 ) time to solve the problem (MSPIT) under weighted $$l_1$$ l 1 norm, in which a minimum cost cut is found in each iteration. We also solve the problem to minimize the cost to upgrade edges such that the length of the shortest path is lower bounded by a value and present an $$O(n^2)$$ O ( n 2 ) algorithm. Finally, we perform some numerical experiments to compare the results obtained by these algorithms.
Keywords: Network interdiction problem; Upgrading critical edges; Shortest path; Weighted $$l_1$$ l 1 norm; Primal dual algorithm; Minimum cost cut (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)
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DOI: 10.1007/s10898-020-00958-0
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