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Machine Learning Assisted Hybrid Cuckoo Search for Predictive Optimization in Renewable Energy Systems. [PDF]

F1000Res
Dalaf N, Abbas IT.
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Breaking the Boundaries of Bayesian Optimization Utilizing Continuous Chemistry Digital Twins. [PDF]

Org Process Res Dev
Chau BT, Miyai Y, Roper TD.
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Stochastic Methods for Global Optimization

American Journal of Mathematical and Management Sciences, 1984
SYNOPTIC ABSTRACTThe most efficient methods for finding the global minimum of an objective function (not necessarily convex) are those that embody stochastic elements. In this survey, we focus on methods that are based on a random sample of points and that use a combination of clustering and local search to identify all the local optima that are ...
A H G Rinnooy Kan
exaly   +2 more sources

Stochastic global optimization as a filtering problem

Journal of Computational Physics, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A STOCHASTIC METHOD FOR GLOBAL OPTIMIZATION [PDF]

, 1980
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.
Boender, C. G. E., Rinnooy Kan, A. H. G., Stougie, L., Timmer, G. T., Boender, C. G. E., Rinnooy Kan, A. H. G., Stougie, L., Timmer, G. T.   +7 more
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A Stochastic Method for Constrained Global Optimization

SIAM Journal on Optimization, 1994
The authors consider a global minimum problem in \(\mathbb{R}^ n\) with finite numbers of both equality and inequality constraints \(h_ i(x)\leq 0\) and \(h_ i(x)= 0\), where the objective function \(F\) and all \(h_ i\) are \(C^ 2\). The problem is solved by considering the unconstrained problem, but with a penalty term that is multiplied by a penalty
Klaus Ritter, Stefan Schäffler
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A Stochastic Algorithm for Constrained Global Optimization

Journal of Global Optimization, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maria Cristina Recchioni, A. Scoccia
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Global Optimization – Stochastic or Deterministic?

2003
Using an aircraft routing problem as a case-study, this paper reports on some practical experience with stochastic and deterministic methods for global optimization. Results show that the deterministic method DIRECT [12] is found to be more reliable than the competing techniques THJ [1] or ECTS [2].
Mike C. Bartholomew-Biggs, Steven C. Parkhurst, Simon P. Wilson 0002   +2 more
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Stochastic approximation for global random optimization

Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334), 2000
A desire with iterative optimization techniques is that the algorithm reach the global optimum rather than get stranded at a local optimum value. One method used to try to assure global convergence is the injection of extra noise terms into the recursion, which may allow the algorithm to escape local optimum points.
John L. Maryak, Daniel C. Chin
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A stochastic probing algorithm for global optimization

Journal of Global Optimization, 1992
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Purushottam W. Laud, L. Mark Berliner, Prem K. Goel   +2 more
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