Great efforts were put to make PyFDE honor the fast in its name.

The table below lists the results obtained by tests/ compared to other differential evolution implementation, namely Solver-DE (C++), lua-de (Lua), and a pure Python 3 version.

All versions were implemented by me, so they all did the same work (DE/rand/1/bin). The JADE implementation takes twice the time per iteration, but usually requires a smaller number of iterations to converge.


This performance test was made specially to measure the speed of the solver’s internal procedures. In most real applications, the performance bottleneck will be in the fitness function.

Implementation Total time (ms) Normalized
solver-de 42 1.00
PyFDE 50 1.19
lua-de (LuaJIT) 78 1.85
lua-de (Lua5.1) 534 12.71
Pure Python 3300 78.57

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