Sentence examples for mathematical programs with from inspiring English sources

However, there is still a scarcity of solution methodologies on fuzzy mathematical programs with fuzzy decision variables.

Mathematical programs with equilibrium constraints (MPECs) form a relatively new and interesting subclass of nonlinear programming problems.

The design models are formulated as mathematical programs with equilibrium constraints, and solved by derivative-free solution algorithms.

Also known as mathematical programs with equilibrium constraints (MPECs), these formulations can be used to model certain classes of discrete events and can be more efficient than a mixed integer formulation.

In this paper, we present feasibility conditions for mathematical programs with affine equilibrium constraints (MPECs) where additional joint constraints are present that must be satisfied by the state and design variables of the problems.

Particular attention is paid to connections with mathematical programs with complementarity constraints, lower level Wolfe duality, semi-smooth approaches, as well as branch and bound techniques in adaptive convexification procedures.

The analysis is cast in its most natural form, namely in mixed static-kinematic variables, and leads to, what is known in the mathematical programing literature, as a mathematical program with equilibrium constraints or MPEC.

The design optimization is a formulation of mathematical programming with equilibrium constraints (MPECs).

It is a continuous bi-level mathematical program with equilibrium constraints.

The problem is formulated as a single-level mathematical program with complementarity constraints (MPCC).

With probit SUE stated as a fixed-point condition, the NDP is a mathematical program with equilibrium constraints (MPEC).