In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints are not linear equalities...

intuition is made formal by the equations in Linear programming: Duality. In nonlinear programming, the constraints are not necessarily linear. Nonetheless...

linear constraints on the variables. Quadratic programming is a type of nonlinear programming. "Programming" in this context refers to a formal procedure...

among them: Linear programming Quadratic programming Nonlinear programming Mixed-integer programming Mixed-integer quadratic programming with or without...

some of the constraints are nonlinear, and some constraints are inequalities, then the problem is a nonlinear programming problem. If all the hard constraints...

The Lagrange multiplier method has several generalizations. In nonlinear programming there are several multiplier rules, e.g. the Carathéodory–John Multiplier...

Linear programming is a special case of mathematical programming (also known as mathematical optimization). More formally, linear programming is a technique...

Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization, also known as Lagrange-Newton method. SQP methods...

optimizer) a software package for linear programming, integer programming, nonlinear programming, stochastic programming, and global optimization. The "What's...

optimization, fractional programming is a generalization of linear-fractional programming. The objective function in a fractional program is a ratio of two functions...

(sometimes called first-order necessary conditions) for a solution in nonlinear programming to be optimal, provided that some regularity conditions are satisfied...

convex programming. Fractional programming studies optimization of ratios of two nonlinear functions. The special class of concave fractional programs can...

computable general equilibrium models for the entire economy. Linear and nonlinear programming have profoundly affected microeconomics, which had earlier considered...

Knitro mixed integer programming (MIP) code offers three algorithms for mixed-integer nonlinear programming (MINLP): Nonlinear Branch and Bound Quesada-Grossmann...

a nonlinear system (or a non-linear system) is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems...

Betts, J. T. (2010). Practical Methods for Optimal Control Using Nonlinear Programming (2nd ed.). Philadelphia, Pennsylvania: SIAM Press. ISBN 978-0-89871-688-7...

Semidefinite programming (SDP) is a subfield of mathematical programming concerned with the optimization of a linear objective function (a user-specified...

large-scale nonlinear programming (NLP), optimization of differential algebraic equations (DAEs), mixed-integer nonlinear programming (MINLP), global...

(1987). "Some NP-complete problems in quadratic and nonlinear programming". Mathematical Programming. 39 (2): 117–129. doi:10.1007/BF02592948. hdl:2027...

3.14(a) in Bertsekas (page 636): Bertsekas, Dimitri P. (1999). Nonlinear Programming (Second ed.). Cambridge, MA.: Athena Scientific. ISBN 1-886529-00-0...

linear-fractional programming (LFP) is a generalization of linear programming (LP). Whereas the objective function in a linear program is a linear function...

among them: Linear programming Quadratic programming Nonlinear programming Mixed-integer programming Mixed-integer quadratic programming with or without...

(BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems. Like the related Davidon–Fletcher–Powell method...

Nonlinear programming — the most general optimization problem in the usual framework Special cases of nonlinear programming: See Linear programming and...

Successive Linear Programming (SLP), also known as Sequential Linear Programming, is an optimization technique for approximately solving nonlinear optimization...

Karush–Kuhn–Tucker conditions, in mathematical optimization of nonlinear programming kkt (Hungarian: közkereseti társaság), a type of general partnership...

user optimum equilibrium can be found by solving the following nonlinear programming problem min ∑ a ∫ 0 v a S a ( x ) d x {\displaystyle \min \sum _{a}{\int...

1971 by Dimitri Bertsekas. The following version is proven in "Nonlinear programming" (1991). Suppose ϕ ( x , z ) {\displaystyle \phi (x,z)} is a continuous...

large-scale problems and solves linear programming, integer programming, nonlinear programming, nonlinear mixed integer programming, dynamic simulation, moving horizon...

convex, and the problem can be solved using linear programming techniques. Nonlinear CCP: For nonlinear systems, the main challenge lies in computing the...