Title
Translating Constraints into QUBOs for the Quadratic Knapsack Problem
Author
Bontekoe, T.
Phillipson, F.
van der Schoot, W.E.
Publication year
2023
Abstract
One of the first fields where quantum computing will likely show its use is optimisation. Many optimisation problems naturally arise in a quadratic manner, such as the quadratic knapsack problem. The current state of quantum computers requires these problems to be formulated as a quadratic unconstrained binary optimisation problem, or QUBO. Constrained quadratic binary optimisation can be translated into QUBOs by translating the constraint. However, this translation can be made in several ways, which can have a large impact on the performance when solving the QUBO. We show six different formulations for the quadratic knapsack problem and compare their performance using simulated annealing. The best performance is obtained by a formulation that uses no auxiliary variables for modelling the inequality constraint.
Subject
Quadratic knapsack problem
Quadratic unconstrained binary optimisation problem
Quantum computing
Simulated annealing
To reference this document use:
http://resolver.tudelft.nl/uuid:a603f5de-ae0e-4daf-a6ca-aa539511773a
TNO identifier
986169
Source
ICCS 2023 - International Conference on Computational Science, Prague 3-5 July 2023
Document type
conference paper