First Choose Problem-Based or Solver-Based Approach - MATLAB & Simulink (original) (raw)
Optimization Toolbox™ has two approaches to solving optimization problems or equations: problem-based and solver-based. Before you start to solve a problem, you must first choose the appropriate approach.
This table summarizes the main differences between the two approaches.
| Approaches | Characteristics |
|---|---|
| Problem-Based Optimization Setup | Easier to create and debug |
| Provides a visual interface; see Optimize Live Editor task | |
| Represents the objective and constraints symbolically | |
| Requires translation from problem form to matrix form, potentially resulting in a longer solution time | |
| Automatically calculates and uses gradients of objective and nonlinear constraint functions in many cases, but does not calculate Hessians; see Automatic Differentiation | |
| See the steps in Problem-Based Optimization Workflow or Problem-Based Workflow for Solving Equations | |
| Basic linear example: Mixed-Integer Linear Programming Basics: Problem-Based or the video Solve a Mixed-Integer Linear Programming Problem using Optimization ModelingBasic nonlinear example: Solve a Constrained Nonlinear Problem, Problem-BasedBasic equation-solving example: Solve Nonlinear System of Equations, Problem-Based | |
| Solver-Based Optimization Problem Setup | Harder to create and debug |
| Provides a visual interface; see Optimize Live Editor task | |
| Represents the objective and constraints as functions or matrices | |
| Does not require translation from problem form to matrix form, potentially resulting in a shorter solution time | |
| Allows direct inclusion of gradient or Hessian, but does not calculate them automatically | |
| Allows use of a Hessian multiply function or Jacobian multiply function to save memory in large problemsSee Quadratic Minimization with Dense, Structured Hessian or Jacobian Multiply Function with Linear Least Squares | |
| See the steps in Solver-Based Optimization Problem Setup | |
| Basic linear example: Mixed-Integer Linear Programming Basics: Solver-BasedBasic nonlinear example:Constrained Nonlinear Problem Using Optimize Live Editor Task or SolverBasic equation-solving examples: Examples |