In optimization design, the objective function depends on design variables, and the range of design variables has various restrictions, such as strength and stiffness. Each constraint can be written as a function containing design variables, which is called a constraint or a design constraint. Because it is a function of design variables, it is also called constraint function.

brief introduction

Mechanical optimization design is generally divided into single-objective optimization problems and multi-objective optimization problems. An optimization problem with only one objective function is called a single objective optimization problem. When multiple target areas are proposed in the same design, it is called multi-objective optimization problem. The more objective functions, the better the comprehensive effect of design, but the more difficult it is to solve.

Generally speaking, the objective function is explicit and implicit. Explicit objective function is an algebraic equation derived from the relationship between design theory or formula and scientific theorem, or a curve equation obtained by curve fitting method according to experimental data; Implicit objective function is the result of program calculation by using finite element analysis method, artificial neural network method or simulation method. There is no obvious function formula, but the function value can be given.