Thanks for the link, Udit, If there is some new algorithm that you think NLopt should adopt, can you please file a github issue with the suggestion and references?
> On Aug 16, 2017, at 6:52 AM, Udit Kumar <udit.v...@gmail.com> wrote: > > Dear NLopt-discuss members, > > Our recent publication titled "Benchmarking NLopt and state-of-the-art > algorithms for continuous global optimization via IACOR" has been published > in Elsevier's Swarm and Evolutionary Computing (DOI: > https://doi.org/10.1016/j.swevo.2015.10.005 > <https://doi.org/10.1016/j.swevo.2015.10.005>). > > Abstract: > This paper presents a comparative analysis of the performance of the > Incremental Ant Colony algorithm for continuous optimization (IACOR), with > different algorithms provided in the NLopt library. The key objective is to > understand how various algorithms in the NLopt library perform in combination > with the Multi-Trajectory Local Search (Mtsls1) technique. A hybrid approach > has been introduced for the local search strategy, by the use of a parameter > that allows for probabilistic selection between Mtsls1 and the NLopt > algorithm. In case of stagnation, a switch is made based on the algorithm > being used in the previous iteration. This paper presents an exhaustive > comparison on the performance of these approaches on Soft Computing (SOCO) > and Congress on Evolutionary Computation (CEC) 2014 benchmarks. For both sets > of benchmarks, we conclude that the best performing algorithm is a hybrid > variant of Mtsls1 with BFGS for local search. > > We hope the paper would be beneficial to the members of this list as a > reference for selection of algorithms to use, as well as a benchmark to > assess their performance on optimization functions of similar nature. > > Thanks > Dr. Udit Kumar > IIT-Delhi, India > _______________________________________________ > NLopt-discuss mailing list > NLopt-discuss@ab-initio.mit.edu > http://ab-initio.mit.edu/cgi-bin/mailman/listinfo/nlopt-discuss
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