Robust Linear Programming with Norm Uncertainty | Zendy

Lei Wang | Zendy; Hong Luo | Zendy

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Robust Linear Programming with Norm Uncertainty

Author(s) -

Lei Wang,

Hong Luo

Publication year - 2014

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2014/209239

Subject(s) - computer science , independent and identically distributed random variables , norm (philosophy) , probabilistic logic , linear programming , convex optimization , algorithm , mathematical optimization , regular polygon , mathematics , statistics , random variable , artificial intelligence , geometry , political science , law

We consider the linear programming problem with uncertainty set described by p,w-norm. We suggest that the robust counterpart of this problem is equivalent to a computationally convex optimization problem. We provide probabilistic guarantees on the feasibility of an optimal robust solution when the uncertain coefficients obey independent and identically distributed normal distributions

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