@article{eprints492,
           title = {An algorithm for approximate multiparametric convex programming},
            year = {2006},
          volume = {35},
           pages = {87--108},
          number = {1},
       publisher = {Springer},
         journal = {Computational Optimization and Applications},
          author = {Alberto Bemporad and Carlo Filippi},
             url = {http://eprints.imtlucca.it/492/},
        abstract = {For multiparametric convex nonlinear programming problems we propose a recursive algorithm for approximating, within a given suboptimality tolerance, the value function and an optimizer as functions of the parameters. The approximate solution is expressed as a piecewise affine function over a simplicial partition of a subset of the feasible parameters, and it is organized over a tree structure for efficiency of evaluation. Adaptations of the algorithm to deal with multiparametric semidefinite programming and multiparametric geometric programming are provided and exemplified. The approach is relevant for real-time implementation of several optimization-based feedback control strategies. }
}