Add to ORKGIn this paper, we consider mixed integer linear programming (MIP) formulations for piecewise linear functions (PLFs) that are evaluated when an indicator variable is turned on. We describe modifications to standard MIP formulations for PLFs with desirable theoretical properties and superior computational performance in this context
Generalized geometric programming (GGP) problems are converted to mixed-integer linear programming (...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
International audienceWe aim at generalizing formulations for non-convex piecewise-linear problems t...
In this paper, we consider mixed integer linear programming (MIP) formulations for piecewise linear ...
We study the modeling of non-convex piecewise linear functions as Mixed Integer Programming (MIP) pr...
In recent years, the increased efficiency of mixed integer linear programming (MILP) software tools ...
AbstractIn an earlier report the concept of a mixed integer minimization model (MIMM) was defined an...
We develop explicit, piecewise-linear formulations of functions f(x):ℝn{mapping}ℝ, n ≤ 3, that are d...
In this chapter, we investigate the smooth representation of the (weakly) efficient solution set of ...
AbstractMixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming ...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
Mixed integer programming (MIP) is commonly used to model indicator constraints, i.e., constraints t...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Resear...
none4We present a new piecewise linear approximation of non-linear optimization problems. It can be ...
Generalized geometric programming (GGP) problems are converted to mixed-integer linear programming (...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
International audienceWe aim at generalizing formulations for non-convex piecewise-linear problems t...
In this paper, we consider mixed integer linear programming (MIP) formulations for piecewise linear ...
We study the modeling of non-convex piecewise linear functions as Mixed Integer Programming (MIP) pr...
In recent years, the increased efficiency of mixed integer linear programming (MILP) software tools ...
AbstractIn an earlier report the concept of a mixed integer minimization model (MIMM) was defined an...
We develop explicit, piecewise-linear formulations of functions f(x):ℝn{mapping}ℝ, n ≤ 3, that are d...
In this chapter, we investigate the smooth representation of the (weakly) efficient solution set of ...
AbstractMixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming ...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
Mixed integer programming (MIP) is commonly used to model indicator constraints, i.e., constraints t...
Mixed logical/linear programming (MLLP) is an extension of mixed integer/linear programming (MILP). ...
Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Resear...
none4We present a new piecewise linear approximation of non-linear optimization problems. It can be ...
Generalized geometric programming (GGP) problems are converted to mixed-integer linear programming (...
The class of continuous piecewise linear (PL) functions represents a useful family of approximants b...
International audienceWe aim at generalizing formulations for non-convex piecewise-linear problems t...