An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization. [PDF]
Comput Intell Neurosci, 2015 Yang ZL, Wu A, Min HQ.
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Quantum‐Enhanced Simulated Annealing Using Rydberg Atoms
Advanced Quantum Technologies, EarlyView.This study experimentally demonstrates that a Rydberg hybrid quantum‐classical algorithm, termed as quantum‐enhanced simulated annealing (QESA), provides a computational time advantage over a classical standalone simulated annealing (SA). This scatter plot represents the comparison of QESA versus SA for the 924 graphs with the sizes N=60$N=60$, 80 and ...
Seokho Jeong, Juyoung Park, Jaewook Ahn
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A New Symmetric Rank One Algorithm for Unconstrained Optimization [PDF]
, 2011 Abbas Al-Bayati, Salah Gazi Shareef
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Leveraging Quantum Annealing for Layout Optimization
Advanced Quantum Technologies, EarlyView.The authors address wind farm layout optimization by formulating it as a QUBO problem using the Jensen wake model. They compare quantum annealing, Gurobi, and QAOA, highlighting trade‐offs between solution quality and computational time. Results show that quantum annealing offers rapid, near‐optimal solutions, making it suitable for fast approximations
Luca Nigro +3 more
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An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization. [PDF]
ScientificWorldJournal, 2013 Celik Y, Ulker E.
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A limited memory BFGS-type method for large-scale unconstrained optimization
, 2008 Yunhai Xiao, Zengxin Wei, Zhiguo Wang
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Unconstrained Optimization of Real Functions in Complex Variables [PDF]
, 2012 Laurent Sorber +2 more
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Unconstrained optimization with MINTOOLKIT for GNU octave
, 2006 The paper documents MINTOOLKIT for GNU Octave. MINTOOLKIT provides functions for minimization and numeric differentiation. The main algorithms are BFGS, LBFGS, and simulated annealing. Examples are given.
Creel, Michael +2 more
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The role of identification in data‐driven policy iteration: A system theoretic study
International Journal of Robust and Nonlinear Control, EarlyView.Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
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An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control. [PDF]
PeerJ Comput SciIbrahim SM +6 more
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