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Alejandro Crema(alejandro.cremaciens.ucv.ve) Abstract: In this paper we present algorithms to approximate the solution for the multiparametric 01mixed integer linear programming problem relative to the objective function. We consider the uncertainty for the parameters that define the cost vector corresponding to a subset of 01variables by assuming that each parameter belongs to a known interval. We suppose that we have enough time to obtain an epsilonoptimal multiparametric solution. Then, when the true cost vector becomes known we can obtain an epsilonoptimal solution quickly. Our algorithms work by solving an appropiate finite sequence of nonparametric problems in such a manner that the solutions of the problems in the sequence provide us with an epsilonoptimal multiparametric solution. Keywords: Integer programming, multiparametric programming, real time. Category 1: Integer Programming ((Mixed) Integer Linear Programming ) Citation: Escuela de ComputaciĆ³n, Facultad de Ciencias, Universidad Central de Venezuela, August 2012. Download: [PDF] Entry Submitted: 08/23/2012 Modify/Update this entry  
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