Quadratic Unconstrained Binary Optimization (QUBO)
Many combinatorial optimization problems can be formulated as Quadratic Unconstrained Binary Optimization (QUBO) problems. These problems include the Traveling Salesperson Problem with QUBO, Capacitated Vehicle Routing Problem, and Feature Selection QUBO (Quadratic Unconstrained Binary Optimization). For background information, see What Is a QUBO Problem?
Also, many current and proposed quantum computers use QUBO (or equivalent Ising) as the problem type. To attempt a quantum solution to a combinatorial optimization problem, you formulate a QUBO problem and then pass the problem to quantum hardware for the solution. Currently, the MATLAB® Support Package for Quantum Computing does not directly support any quantum hardware for solving QUBO problems.
- What Is a QUBO Problem?
This topic introduces the basics of Quadratic Unconstrained Binary Optimization (QUBO) problems.
- Workflow for QUBO Problems
Learn the steps for formulating and solving a QUBO problem.
- Constraints in QUBO Problems
Include constraints in a QUBO problem by adding penalty terms.
- Tabu Search Algorithm
Learn about the tabu search heuristic algorithm used to solve QUBO problems.
- Verify Optimality by Solving QUBO as MILP
Convert a QUBO problem to a mixed-integer linear programming (MILP) problem, and solve the problem using
- Traveling Salesperson Problem with QUBO
Convert a Traveling Salesperson Problem (TSP) to a QUBO problem and solve the problem.
- Capacitated Vehicle Routing Problem
Express and solve a capacitated vehicle routing problem using QUBO.
- Feature Selection QUBO (Quadratic Unconstrained Binary Optimization)
Find the most relevant predictors in a data set using a QUBO problem formulation.