  This paper proposes a new numerical optimization algorithm inspired by the
strawberry plant for solving complicated engineering problems. Plants like
strawberry develop both runners and roots for propagation and search for water
resources and minerals. In these plants, runners and roots can be thought of as
tools for global and local searches, respectively. The proposed algorithm has
three main differences with the trivial nature-inspired optimization
algorithms: duplication-elimination of the computational agents at all
iterations, subjecting all agents to both small and large movements from the
beginning to end, and the lack of communication (information exchange) between
agents. Moreover, it has the advantage of using only three parameters to be
tuned by user. This algorithm is applied to standard test functions and the
results are compared with GA and PSO. The proposed algorithm is also used to
solve an open problem in the field of robust control theory. These simulations
show that the proposed algorithm can very effectively solve complicated
optimization problems.
