This repository contains MATLAB implementations of a variety of popular nonlinear programming algorithms, many of which can be found in Numerical Optimization by Nocedal and Wright, a text that I ...

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...

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.

Mixed-integer nonlinear programming (MINLP) optimisation constitutes a critical methodology in tackling complex decision-making problems where both discrete choices and continuous variables are ...

The problems are usually formulated as mixed-integer nonlinear programming problems. Although many optimization approaches have been developed to solve mixed-integer nonlinear programming problems, ...

Another direction of improving optimization-based classification is to develop nonlinear models by constructing nonlinear objectives, such as the Multiple Criteria Quadratic Programming (MCQP), a ...

The most important nonlinear programming methods, complementarity algorithms ... In Section 2 some applications and reformulations of optimization problems as MPLCC are surveyed. Section 3 addresses ...

Abstract: Social cognitive optimization (SCO) for solving nonlinear programming problems (NLP) is presented based on human intelligence with the social cognitive theory (SCT). Experiments comparing ...

The outcomes of our optimization show that cost-optimal design generally increases cell length while decreasing cell pair number and operating voltage with an increase in salinity. These trends are ...