Learn the main differences between linear and nonlinear programming, examples of problems that require each method, and tips to identify the best method.

We considered the nonlinear programming problems with interval grey number in the objective function when the distribution of grey number is known, and when it is unknown, according to historical data ...

This paper aims at utilizing the dynamic behavior of artificial neural networks to solve nonlinear multilevel programming (MLP) problems. Across complementarily slackness conditions base on entropic ...

Second, the conversion to a single-objective optimization problem involves additional constraints. Third, since most real-world goal programming problems involve nonlinear criterion functions, the ...

Abstract. In this paper, some interval valued programming problems are discussed. The solution concepts are adopted fromWu [7] and Chalco-Cano et al. [34]. By considering generalized Hukuhara ...

In this paper, a feasible path-based branch and bound (B&B) algorithm is proposed to solve mixed-integer nonlinear programming problems with highly nonconvex nature through integration of the ...

Solving nonconvex nonlinear programming and mixed-integer nonlinear programming problems with adaptive random search R. L. Salcedo ...

ABSTRACT: A dual for a nonlinear programming problem in the presence of equality and inequality constraints which represent many realistic situation, is formulated which uses Fritz John optimality ...

Gas Network Optimization and Nonlinear Programming Publication Trend The graph below shows the total number of publications each year in Gas Network Optimization and Nonlinear Programming.

Linear and nonlinear programming are two types of optimization methods that can help you find the best solution to a problem involving decision variables, constraints, and an objective function.