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Article Dans Une Revue Discrete Applied Mathematics Année : 2010

Robust Network Optimization under Polyhedral Demand Uncertainty is NP-Hard

Michel Minoux
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Résumé

Minimum cost network design/dimensioning problems where feasibility has to be ensured w.r.t. a given (possibly infinite) set of scenarios of requirements form an important subclass of robust LP problems with right-hand side uncertainty. Such problems arise in many practical contexts such as Telecommunications, logistic networks, power distribution networks, etc. Though some evidence of the computational difficulty of such problems can be found in the literature, no formal NP-hardness proof was available up to now. In the present paper, this pending complexity issue is settled for all robust network optimization problems featuring polyhedral demand uncertainty, both for the single-commodity and multicommodity case, even if the corresponding deterministic versions are polynomially solvable as regular (continuous) linear programs. A new family of polynomially solvable instances is also discussed.

Dates et versions

hal-01170333 , version 1 (01-07-2015)

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Michel Minoux. Robust Network Optimization under Polyhedral Demand Uncertainty is NP-Hard. Discrete Applied Mathematics, 2010, 158 (5), pp.597-603. ⟨10.1016/j.dam.2009.09.025⟩. ⟨hal-01170333⟩
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