Boender-Rinnooy-Stougie-Timmer algorithm (BRST) is an optimization algorithm suitable for finding global optimum of black box functions. In their paper Boender et al describe their method as a stochastic method involving a combination of sampling, clustering and local search, terminating with a range of confidence intervals on the value of the global minimum. The algorithm of Boender et al has been modified by Timmer . Timmer considered several clustering methods. Based on experiments a method named "multi level single linkage" was deemed most accurate.
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| - Boender-Rinnooy-Stougie-Timmer algorithm (BRST) is an optimization algorithm suitable for finding global optimum of black box functions. In their paper Boender et al describe their method as a stochastic method involving a combination of sampling, clustering and local search, terminating with a range of confidence intervals on the value of the global minimum. The algorithm of Boender et al has been modified by Timmer . Timmer considered several clustering methods. Based on experiments a method named "multi level single linkage" was deemed most accurate. Csendes' algorithms are implementations of the algorithm of [Boender et al] and originated the public-domain software product GLOBAL. The local algorithms used are a random direction, linear search algorithm also used by Törn, and a quasi--Newton algorithm not using the derivative of the function. The results show the dependence of the result on the auxiliary local algorithm used. (en)
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| - Boender-Rinnooy-Stougie-Timmer algorithm (BRST) is an optimization algorithm suitable for finding global optimum of black box functions. In their paper Boender et al describe their method as a stochastic method involving a combination of sampling, clustering and local search, terminating with a range of confidence intervals on the value of the global minimum. The algorithm of Boender et al has been modified by Timmer . Timmer considered several clustering methods. Based on experiments a method named "multi level single linkage" was deemed most accurate. (en)
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