Evaluations of An Algorithm for Large Multivariate Optimization
2021 ◽
Vol 2068
(1)
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pp. 012026
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Abstract Many simulation-driven engineering and scientific problems require finding an optimum of a function with many variables. Such settings pose a challenge for standard algorithms due to the large search space which in turn can lead to poor final results. Therefore this paper proposes a new simplified approach in which the dimension of the problem is dynamically reduced during the search to formulate a problem of lower size (dimension) which is easier to solve. A main novelty of the algorithm is its simplicity. Numerical experiments show the potential of this approach.
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2017 ◽
Vol 137
(9)
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pp. 1266-1278
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2018 ◽
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2013 ◽
Vol 43
(1)
◽
pp. 47-60
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