Results 101 to 110 of about 3,222 (193)

Application of Quantum Annealing to Nurse Scheduling Problem

, 2019
Quantum annealing is a promising heuristic method to solve combinatorial optimization problems, and efforts to quantify performance on real-world problems provide insights into how this approach may be best used in practice.
Humble, Travis S., Ikeda, Kazuki, Nakamura, Yuma   +2 more
core  

Solving QUBO problems with cP systems

Journal of Membrane Computing
AbstractP systems with compound terms (cP systems) have been proposed by Radu Nicolescu in 2018. These expressive cP systems have been used to solve well-known NP-complete problems efficiently, such as the Hamiltonian path, traveling salesman, 3-coloring, and software verification problems.
Lucie Ciencialová, Michael J. Dinneen, Radu Nicolescu, Ludek Cienciala   +3 more
openaire   +1 more source

Student Surpasses the Teacher: Apprenticeship Learning for Quadratic Unconstrained Binary Optimisation

Algorithms
This study introduces a novel train-and-test approach referred to as apprenticeship learning (AL) for generating selection hyper-heuristics to solve the Quadratic Unconstrained Binary Optimisation (QUBO) problem.
Jack Cakebread, Warren G. Jackson, Daniel Karapetyan, Andrew J. Parkes, Ender Özcan   +4 more
doaj   +1 more source

Construction of SubQUBOs by K-Means Clustering of QUBO Variables

IEEE Access
Ising machines are specialized solvers for combinatorial optimization problems (COPs), which are typically formulated as quadratic unconstrained binary optimization (QUBO) models.
Yuko Kamishima, Shuta Kikuchi, Shu Tanaka   +2 more
doaj   +1 more source

MOCQA: A Multi-Core Optimizer for Constrained Quadratic Assignment

IEEE Access
Despite advances in general processing hardware, optimization of NP-hard problems remains a time and compute-intensive task, with the end of Dennard Scaling leading to the increased development of domain-specific hardware in this area.
Mohammad Bagherbeik, Parastoo Ashtari, Kouichi Kanda, Hirotaka Tamura, Ali Sheikholeslami   +4 more
doaj   +1 more source

Penalty Weights in QUBO Formulations: Permutation Problems

, 2022
Optimisation algorithms designed to work on quantum computers or other specialised hardware have been of research interest in recent years. Many of these solver can only optimise problems that are in binary and quadratic form. Quadratic Unconstrained Binary Optimisation (QUBO) is therefore a common formulation used by these solvers.
openaire   +2 more sources

An Optimal Constraint for QUBO Models

, 2021
8 pages, 16 images, 4 ...
openaire   +2 more sources

QUBO Formulations and Quantum Optimization for the Multi-Dimensional Knapsack Problem With Conflict, Forcing, and Precedence Constraints

IEEE Access
Constrained knapsack variants are well-suited for QUBO-based quantum optimization, but adding logical relations can inflate the binary model and complicate penalty selection.
Evren Guney, Joachim Ehrenthal
doaj   +1 more source

QUBO Formulation Using Sequence Pair With Search Space Restriction for Rectangle Packing Problem

IEEE Access
The development of quantum annealing has stimulated interest in solving NP-hard problems, including various industrial problems, such as quadratic unconstrained binary optimization (QUBO), with specialized solvers.
Akihisa Okada, Keisuke Otaki, Tadayoshi Matsumori, Hiroaki Yoshida, Kotaro Terada, Nozomu Togawa   +5 more
doaj   +1 more source

Application of quantum computing to temporal aggregation for efficient capacity expansion in power systemsOPSD

International Journal of Electrical Power & Energy Systems
Capacity expansion planning (CEP) requires full-year, hourly time series to capture variability in load and renewable generation, but this temporal resolution makes optimization problems computationally challenging.
Ankana Singha, Sambeet Mishra, Miadreza Shafie-khah   +2 more
doaj   +1 more source