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Capacity inverse minimum cost flow problems under the weighted Hamming distance

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Abstract

Given a network N(VAuc) and a feasible flow \(x^0\), the inverse minimum cost flow problem is to modify the capacity vector or the cost vector as little as possible to make \(x^0\) form a minimum cost flow of the network. The modification can be measured by different norms. In this paper, we consider the capacity inverse minimum cost flow problems under the weighted Hamming distance, where we use the weighted Hamming distance to measure the modification of the arc capacities. Both the sum-type and the bottleneck-type cases are considered. For the former, it is shown to be APX-hard due to the weighted feedback arc set problem. For the latter, we present a strongly polynomial algorithm which can be done in \(O(n\cdot m^2)\) time.

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Acknowledgments

The authors wish to thank the anonymous referees whose valuable comments allowed us to improve the paper. This research is supported by the National Natural Science Foundation of China (Grant No. 11001232),Fujian Provincial Natural Science Foundation of China (Grant No. 2012J01021) and Fundamental Research Funds for the Central Universities (Grant No. 2010121004).

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Correspondence to Longcheng Liu.

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Liu, L., Yao, E. Capacity inverse minimum cost flow problems under the weighted Hamming distance. Optim Lett 10, 1257–1268 (2016). https://doi.org/10.1007/s11590-015-0919-y

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  • DOI: https://doi.org/10.1007/s11590-015-0919-y

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