Quadratic Unconstrained Binary Optimization (QUBO)

Quadratic Unconstrained Binary Optimization (QUBO) for combinatorial optimization problems
Since R2023a

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.

Objects

quboQuadratic Unconstrained Binary Optimization
quboResultResult of solving QUBO problem
tabuSearchTabu search algorithm for QUBO solve
tabuSearchResultResult of solve for Tabu search algorithm
qaoaQuantum approximate optimization algorithm (QAOA) for solving QUBO problem (Since R2024b)
qaoaResultResult of solving QUBO problem using QAOA (Since R2024b)

Functions

evaluateObjectiveEvaluate QUBO (Quadratic Unconstrained Binary Optimization) objective
solveSolve QUBO (Quadratic Unconstrained Binary Optimization) problem
maxcut2quboConvert max-cut problem to QUBO (Quadratic Unconstrained Binary Optimization) (Since R2024b)
qubo2isingConvert QUBO problem to Ising observable (Since R2024b)

Topics

Featured Examples

Solve Max-Cut Problem Using QAOA

Solve Max-Cut Problem Using QAOA

Use the Quantum Approximate Optimization Algorithm (QAOA) to solve max-cut problems.