  This Ph.D. thesis discusses advanced design issues of the evolutionary-based
algorithm \textit{"Coral Reef Optimization"}, in its Substrate-Layer (CRO-SL)
version, for optimization problems in Engineering Applications. The problems
that can be tackled with meta-heuristic approaches is very wide and varied, and
it is not exclusive of engineering. However we focus the Thesis on it area, one
of the most prominent in our time. One of the proposed application is battery
scheduling problem in Micro-Grids (MGs). Specifically, we consider an MG that
includes renewable distributed generation and different loads, defined by its
power profiles, and is equipped with an energy storage device (battery) to
address its programming (duration of loading / discharging and occurrence) in a
real scenario with variable electricity prices. Also, we discuss a problem of
vibration cancellation over structures of two and four floors, using Tuned Mass
Dampers (TMD's). The optimization algorithm will try to find the best solution
by obtaining three physical parameters and the TMD location. As another related
application, CRO-SL is used to design Multi-Input-Multi-Output Active Vibration
Control (MIMO-AVC) via inertial-mass actuators, for structures subjected to
human induced vibration. In this problem, we will optimize the location of each
actuator and tune control gains. Finally, we tackle the optimization of a
textile modified meander-line Inverted-F Antenna (IFA) with variable width and
spacing meander, for RFID systems. Specifically, the CRO-SL is used to obtain
an optimal antenna design, with a good bandwidth and radiation pattern, ideal
for RFID readers. Radio Frequency Identification (RFID) has become one of the
most numerous manufactured devices worldwide due to a reliable and inexpensive
means of locating people. They are used in access and money cards and product
labels and many other applications.
