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Use Random Keys
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Implement Lévy Flights like Yang on their example of Cuckoo Search
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Use rk2al(). Some functions, like for generation of new solutions, should be modified.
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Test two generation methods independently. Later, test both together. If it's not better, left one.
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The RUR method is bullshit. Use another criteria to determine which solution is better.
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To end the algorithm, look when the best cost does not improve in 200 iterations (it could be a bigger or smaller number, depending on the problem). Analize for particular cases if that number can be setted automatically
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The MPE measures dispersion. Another unuseful parameter. In some cases, when the cost doesn't change in 200 iterations, the simulation can be finalized.
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Implement a comparison between the dispersion with the upper bound as a measurement parameter.
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Compare with a Genetic Algorithm.
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Improve performance using Numpy.
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Dynamic allocation of variables
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Merge functions into one library file (of load files)
- Organize the files into /src, /include, /tests and, may be, others.