Optimization techniques are used to find a set of design parameters that give the best possible result. There are two key components in an optimization problem:
The objective function calculates the desired quantity to be minimized or maximized. Constraints can be added that limit the possible values for the design parameters.
Mathematical Modeling with Optimization, Part 1
Transform a problem description into a mathematical program that can be solved using optimization, using a steam and electric power plant example.
Mathematical Modeling with Optimization, Part 2
Solve a linear program using Optimization Toolbox™ solvers, using a steam and electric power plant example.
You can access Optimization Toolbox functions and solver options programmatically, or with the Optimization app.
The Optimization app simplifies common optimization tasks. It enables you to:
Introduction to Optimization Graphical User Interface
Set up and run optimization problems and visualize intermediate and final results.
Optimization Toolbox contains different solvers for different types of objectives and constraints. The Optimization Decision Table helps you choose the best solver for your problem.
Solver options enable you to tune or modify the optimization process and visualize solver progress. Setting options can be done programmatically or with the Optimization app.