Before you begin to solve an optimization problem, you must choose the appropriate approach: problem-based or solver-based. For details, see First Choose Problem-Based or Solver-Based Approach.
For the problem-based approach, create problem variables, and then
represent the objective function and constraints in terms of these symbolic
variables. For the problem-based steps to take, see Problem-Based Optimization Workflow. To
solve the resulting problem, use solve.
For the solver-based steps to take, including defining the objective
function and constraints, and choosing the appropriate solver, see Solver-Based Optimization Problem Setup. To solve the
resulting problem, use intlinprog when there are
integer constraints, or use linprog when there are no
integer constraints.
| Optimize | Optimize or solve equations in the Live Editor |
Mixed-Integer Linear Programming Basics: Problem-Based
Simple example of mixed-integer linear programming.
Factory, Warehouse, Sales Allocation Model: Problem-Based
This example shows how to set up and solve a mixed-integer linear programming problem.
Traveling Salesman Problem: Problem-Based
This example shows how to use binary integer programming to solve the classic traveling salesman problem.
Optimal Dispatch of Power Generators: Problem-Based
This example shows how to schedule two gas-fired electric generators optimally, meaning to get the most revenue minus cost.
Office Assignments by Binary Integer Programming: Problem-Based
This example shows how to solve an assignment problem by binary integer programming using the optimization problem approach.
Mixed-Integer Quadratic Programming Portfolio Optimization: Problem-Based
This example shows how to solve a Mixed-Integer Quadratic Programming (MIQP) portfolio optimization problem using the problem-based approach.
Cutting Stock Problem: Problem-Based
This example shows how to solve a cutting stock problem using linear programming with an integer linear programming subroutine.
Minimize Makespan in Parallel Processing
Minimize the maximum time for a set of processors to complete a group of tasks.
Solve Sudoku Puzzles Via Integer Programming: Problem-Based
This example shows how to solve a Sudoku puzzle using binary integer programming.
Mixed-Integer Linear Programming Basics: Solver-Based
Simple example of mixed-integer linear programming.
Factory, Warehouse, Sales Allocation Model: Solver-Based
Example of optimizing logistics in a small supply chain.
Traveling Salesman Problem: Solver-Based
The classic traveling salesman problem, with setup and solution.
Optimal Dispatch of Power Generators: Solver-Based
Example showing how to schedule power generation when there is a cost for activation.
Office Assignments by Binary Integer Programming: Solver-Based
Solve an assignment problem using binary integer programming.
Mixed-Integer Quadratic Programming Portfolio Optimization: Solver-Based
Example showing how to optimize a portfolio, a quadratic programming problem, with integer and other constraints.
Cutting Stock Problem: Solver-Based
Solve a cutting stock problem using linear programming with an integer programming subroutine.
Solve Sudoku Puzzles Via Integer Programming: Solver-Based
Sudoku is a type of puzzle that you can solve using integer linear programming.
Set Up a Linear Program, Problem-Based
Linear problem formulation using the problem-based approach.
Maximize Long-Term Investments Using Linear Programming: Problem-Based
Optimize a deterministic multiperiod investment problem using linear programming and the problem-based approach.
Create Multiperiod Inventory Model in Problem-Based Framework
Create an inventory model, where stock is carried between time periods, in the problem-based approach.
Set Up a Linear Program, Solver-Based
Problem formulation using the solver-based approach.
Typical Linear Programming Problem
This example shows the solution of a typical linear programming problem.
Investigate Linear Infeasibilities
Find out which linear constraints cause a problem to be infeasible.
Maximize Long-Term Investments Using Linear Programming: Solver-Based
Optimize a deterministic multiperiod investment problem using linear programming.
Problem-Based Optimization Algorithms
How the optimization functions and objects solve optimization problems.
Supported Operations on Optimization Variables and Expressions
Lists all available mathematical and indexing operations on optimization variables and expressions.
Minimizing a linear objective function in n dimensions with only linear and bound constraints.
Mixed-Integer Linear Programming Algorithms
The algorithms used for solution of mixed-integer linear programs.
Optimization Options Reference
Explore optimization options.
Tuning Integer Linear Programming
Steps for improving solutions or solution time.
intlinprog Output Function and Plot Function Syntax
How to monitor the progress of the intlinprog solution
process.