  Flower Pollination Algorithm (FPA) is the new breed of metaheuristic for the
general optimization problem. In this paper, an improved algorithm based on
Flower Pollination Algorithm (FPA), called imFPA, has been proposed. In imFPA,
the static selection probability is replaced by the dynamic solution selection
probability in order to enhance the diversification and intensification of the
overall search process. Experimental adoptions on combinatorial t- way test
suite generation problem (where t indicates the interaction strength) show that
imFPA produces very competitive results as compared to existing strategies.
