In this book, a novel optimization method inspired by a paradigm
from nature is introduced. The chemical reactions are used as a
paradigm to propose an optimization method that simulates these
natural processes. The proposed algorithm is described in detail
and then a set of typical complex benchmark functions is used to
evaluate the performance of the algorithm. Simulation results show
that the proposed optimization algorithm can outperform other
methods in a set of benchmark functions.
This chemical reaction optimization paradigm is also applied to
solve the tracking problem for the dynamic model of a unicycle
mobile robot by integrating a kinematic and a torque controller
based on fuzzy logic theory. Computer simulations are presented
confirming that this optimization paradigm is able to outperform
other optimization techniques applied to this particular robot
application.
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