Improved Filters and Randomized Drivers for Multi-start Global Optimization
نویسندگان
چکیده
منابع مشابه
Dynamic filters and randomized drivers for the multi-start global optimization algorithm MSNLP
We present results of extensive computational tests of i) comparing dynamic filters (first mentioned in an earlier publication addressing a feasibility seeking algorithm) with static filters and ii) stochastic starting point generators (" drivers ") for a multi-start global optimization algorithm called MSNLP. We show how the widely used NLP local solvers CONOPT and SNOPT compare when used in t...
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