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Generalized Simulated Annealing
, 2017 Many problems in mathematics, statistics, finance, biology, pharmacology, physics, applied mathematics, economics, and chemistry involve the determination of the global minimum of multidimensional real-valued functions.
Yang Xiang +2 more
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Simulated annealing for earthquake location
地震科学进展, 2021 Earthquake location is one of the most basic tasks of seismology research such as earthquake monitoring and earthquake prediction. Identification of earthquake location with high efficiency and accuracy is of great significance to the development of ...
Xiaohan Li, Guangke Li, Dawei Jiao
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Simulated Annealing: a Review and a New Scheme
Symposium on Software Performance, 2021 Finding the global minimum of a nonconvex optimization problem is a notoriously hard task appearing in numerous applications, from signal processing to machine learning.
Thomas Guilmeau +2 more
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Quantum Simulated Annealing Algorithm [PDF]
Engineering and Technology Journal, 2010 Simulated annealing (SA) has been considered as a good tool for searchand optimization problems which represent the abstraction of obtaining thecrystalline structure through a physical process. This algorithm works sequentiallythat the current state will
Rana Fareed Ghani
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JEMMME (Journal of Energy, Mechanical, Material, and Manufacturing Engineering), 2023 Simulated annealing is an optimization method adapted from the annealing process. The optimization process using simulated annealing method is done by mapping the elements of physical coolant process onto the elements of optimization problem. This method
Yosua Heru Irawan, Po Ting Lin
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Generalized simulated annealing [PDF]
Physica A: Statistical Mechanics and its Applications, 1996 13 pages, latex, 4 figures available upon request with the authors.
Tsallis, Constantino +1 more
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Discover Internet of Things, 2023 The multi-objective grasshopper optimization algorithm (MOGOA) is a relatively new algorithm inspired by the collective behavior of grasshoppers, which aims to solve multi-objective optimization problems in IoT applications.
Faria Sajjad +8 more
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Strategic Portfolio Optimization Using Simulated, Digital, and Quantum Annealing
Applied Sciences, 2022 In this work, we introduce a new workflow to solve portfolio optimization problems on annealing platforms. We combine a classical preprocessing step with a modified unconstrained binary optimization (QUBO) model and evaluate it using simulated annealing (
Jonas Lang +2 more
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IEEE Access, 2023 Simulated Quantum Annealing (SQA) is a heuristic algorithm which can solve Quadratic Unconstrained Binary Optimization (QUBO) problems by emulating the exploration of the solution space done by a quantum annealer.
Deborah Volpe +3 more
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Unsupervised Paraphrasing by Simulated Annealing [PDF]
Annual Meeting of the Association for Computational Linguistics, 2019 We propose UPSA, a novel approach that accomplishes Unsupervised Paraphrasing by Simulated Annealing. We model paraphrase generation as an optimization problem and propose a sophisticated objective function, involving semantic similarity, expression ...
Xianggen Liu +5 more
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