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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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The GLOBAL optimization method revisited
Optimization Letters, 2007 Peer ...
Tibor Csendes +3 more
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NeuralMinimizer: A Novel Method for Global Optimization
Information, 2023 The problem of finding the global minimum of multidimensional functions is often applied to a wide range of problems. An innovative method of finding the global minimum of multidimensional functions is presented here. This method first generates an approximation of the objective function using only a few real samples from it.
Ioannis G. Tsoulos +3 more
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Minorant Methods of Stochastic Global Optimization [PDF]
Cybernetics and Systems Analysis, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Norkin, V. I., Onishchenko, B. O.
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Homotopy optimization methods for global optimization. [PDF]
, 2005 We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method differs from previous homotopy and continuation methods in that its aim is to find a minimizer for each of a set of values of the homotopy parameter, rather than to follow a path of minimizers.
Dunlavy, Daniel M. +4 more
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Concurrent stochastic methods for global optimization [PDF]
Mathematical Programming, 1990 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Richard H. Byrd +3 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
Norkin, V.I. +2 more
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On the Global Convergence of Particle Swarm Optimization Methods
Applied Mathematics & Optimization, 2023 AbstractIn this paper we provide a rigorous convergence analysis for the renowned particle swarm optimization method by using tools from stochastic calculus and the analysis of partial differential equations. Based on a continuous-time formulation of the particle dynamics as a system of stochastic differential equations, we establish convergence to a ...
Huang, H, Qiu, J, Riedl, K
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Black Box Optimization Benchmarking of the GLOBAL Method [PDF]
Evolutionary Computation, 2012 GLOBAL is a multi-start type stochastic method for bound constrained global optimization problems. Its goal is to find the best local minima that are potentially global. For this reason it involves a combination of sampling, clustering, and local search.
László Pál +3 more
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Accelerations for a variety of global optimization methods [PDF]
Journal of Global Optimization, 1994 This paper studies acceleration techniques for a class of deterministic algorithms for global optimization. The acceleration techniques are applicable if the functions to be minimized have certain smoothness properties. They use the Lipschitz constant of the function and derivative information to construct better lower envelopes for the function.
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