Results 31 to 40 of about 178 (50)
Evaluating the job shop scheduling problem on a D-wave quantum annealer
Job Shop Scheduling is a combinatorial optimization problem of particular importance for production environments where the goal is to complete a production task in the shortest possible time given limitations in the resources available.
Costantino Carugno +2 more
doaj +1 more source
Beyond optimization: Harnessing quantum annealer dynamics for machine learning
Quantum annealing is typically regarded as a tool for combinatorial optimization, but its coherent dynamics also offer potential for machine learning.
Akitada Sakurai +5 more
doaj +1 more source
Quantum annealing algorithms for Boolean tensor networks
Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality heuristic solutions of NP-hard problems.
Elijah Pelofske +4 more
doaj +1 more source
Quantum annealing has gained considerable attention because it can be applied to combinatorial optimization problems, which have numerous applications in logistics, scheduling, and finance.
Michiya Kuramata +2 more
doaj +1 more source
Power flow (PF) analysis is a foundational computational method to study the flow of power in an electrical network. This analysis involves solving a set of non-linear and non-convex differential-algebraic equations.
Zeynab Kaseb +3 more
doaj +1 more source
Efficient partition of integer optimization problems with one-hot encoding
Quantum annealing is a heuristic algorithm for solving combinatorial optimization problems, and hardware for implementing this algorithm has been developed by D-Wave Systems Inc.
Shuntaro Okada +2 more
doaj +1 more source
Effective prime factorization via quantum annealing by modular locally-structured embedding
This paper investigates novel techniques to solve prime factorization by quantum annealing (QA). First, we present a very-compact modular encoding of a multiplier circuit into the architecture of current D-Wave QA devices.
Jingwen Ding +2 more
doaj +1 more source
In this article, we propose a postprocessing variationally scheduled quantum algorithm (pVSQA) for solving constrained combinatorial optimization problems (COPs).
Tatsuhiko Shirai, Nozomu Togawa
doaj +1 more source
Physics-Inspired Optimization for Quadratic Unconstrained Problems Using a Digital Annealer
The Fujitsu Digital Annealer is designed to solve fully connected quadratic unconstrained binary optimization (QUBO) problems. It is implemented on application-specific CMOS hardware and currently solves problems of up to 1,024 variables.
Maliheh Aramon +7 more
doaj +1 more source
Classical criticality via quantum annealing
Quantum annealing provides a powerful platform for simulating magnetic materials and realizing statistical physics models, presenting a compelling alternative to classical Monte Carlo methods.
Pratik Sathe +5 more
doaj +1 more source

