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Robust minimum cost flow problem under consistent flow constraints
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DOI：10.1007/s10479-021-04426-0.png)
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The robust minimum cost flow problem under consistent flow constraints (RobMCF()) is a new extension of the minimum cost flow (MCF) problem. In the RobMCF() problem, we consider demand and supply that are subject to uncertainty. For all demand realizations, however, we require that the flow value on an arc needs to be equal if it is included in the predetermined arc set given. The objective is to find feasible flows that satisfy the equal flow requirements while minimizing the maximum occurring cost among all demand realizations. In the case of a finite discrete set of scenarios, we derive structural results which point out the differences with the polynomial time solvable MCF problem in networks with integral demands, supplies, and capacities. In particular, the Integral Flow Theorem of Dantzig and Fulkerson does not hold. For this reason, we require integral flows in the entire paper. We show that the RobMCF() problem is strongly N-hard on acyclic digraphs by a reduction from the (3, B2)-SAT problem. Further, we demonstrate that the RobMCF problem is weakly NP-hard on series-parallel digraphs by providing a reduction from PARTITION. If in addition the number of scenarios is constant, we propose a pseudo-polynomial algorithm based on dynamic programming. Finally, we present a special case on series-parallel digraphs for which we can solve the RobMCF() problem in polynomial time.
Keyword:
Minimum cost flow problem
Equal flow problem
Robust flows
Series-parallel digraphs
Dynamic programming
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4.5
论文数:
8.0K
被引数:
2.1W
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