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Stochastic Smoothing Methods for Nonsmooth Global Optimization [PDF]
Кібернетика та комп'ютерні технології, 2020 . The paper presents the results of testing the stochastic smoothing method for global optimization of a multiextremal function in a convex feasible subset of Euclidean space.
V.I. Norkin
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A stochastic method for global optimization [PDF]
Mathematical Programming, 1982 A stochastic method for global optimization is described and evaluated. The method involves a combination of sampling, clustering and local search, and terminates with a range of confidence intervals on the value of the global optimum. Computational results on standard test functions are included as well.
Leen Stougie, Rinnooy Kan A H G
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Non-Stationary Stochastic Global Optimization Algorithms
Algorithms, 2022 Studying the theoretical properties of optimization algorithms such as genetic algorithms and evolutionary strategies allows us to determine when they are suitable for solving a particular type of optimization problem. Such a study consists of three main
Jonatan Gomez, Andres Rivera
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On Local Convergence of Stochastic Global Optimization Algorithms [PDF]
Lecture Notes in Computer Science, 2021 AbstractIn engineering optimization with continuous variables, the use of Stochastic Global Optimization (SGO) algorithms is popular due to the easy availability of codes. All algorithms have a global and local search character, where the global behaviour tries to avoid getting trapped in local optima and the local behaviour intends to reach the lowest
Eligius M T Hendrix +2 more
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A branch and bound method for stochastic global optimization [PDF]
Mathematical Programming, 1998 A stochastic branch and bound method for solving stochastic global optimization problems is proposed. As in the deterministic case, the feasible set is partitioned into compact subsets. To guide the partitioning process the method uses stochastic upper and lower estimates of the optimal value of the objective function in each subset. Convergence of the
V I Norkin +2 more
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Stochastic global optimization algorithms: A systematic formal approach [PDF]
Information Sciences, 2019 30 pages, 0 ...
Jonatan Gomez
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A New Stochastic Process of Prestack Inversion for Rock Property Estimation
Applied Sciences, 2022 In order to enrich the current prestack stochastic inversion theory, we propose a prestack stochastic inversion method based on adaptive particle swarm optimization combined with Markov chain Monte Carlo (MCMC).
Long Yin +6 more
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Comparative study between local and global optimization for Heston model
Ratio Mathematica, 2022 The objective of this study is to estimate the calibration parameters of the Heston stochastic volatility model by the two optimization methods: local and global, then to compare their performances and finally to recommend one of the two methods.
Mohammed Bouasabah
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On the Investigation of Stochastic Global Optimization Algorithms [PDF]
Journal of Global Optimization, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baritompa, B., Hendrix, E.M.T.
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Stochastic Triad Topology Based Particle Swarm Optimization for Global Numerical Optimization
Mathematics, 2022 Particle swarm optimization (PSO) has exhibited well-known feasibility in problem optimization. However, its optimization performance still encounters challenges when confronted with complicated optimization problems with many local areas.
Qiang Yang +6 more
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