1) Establishing a mathematical model, that is, using mathematical language to describe the optimization problem. The mathematical relationships in the model reflect the goals and various constraints to be achieved in the optimization problem.
2) Mathematical solution After the mathematical model is built, choose a reasonable optimization method to solve it.
Using Matlab's optimization toolbox, you can solve linear programming, nonlinear programming and multi-objective programming problems. Specifically, it includes linear and nonlinear minimization, maximinization, quadratic programming, semi-infinite problems, solution of linear and nonlinear equations (sets), and linear and nonlinear least squares problems. In addition, the toolbox also provides solving methods for medium and large-scale topics such as linear and nonlinear minimization, equation solving, curve fitting, quadratic programming, etc., providing a more convenient and faster way for the practical application of optimization methods in engineering. . Interested friends can come and take a look