This paper proposes a hybrid task scheduling method based on the invasive weed bat algorithm upon dual-subpopulation to achieve objective of minimal task implementation time for equipment support groups cooperative task scheduling. The mathematical model is constructed considering complex constrains such as task sequential logical relationship, implementation quality, occupancy conflicts and capability renewal mechanism of support groups. Firstly, the good-point set theory is used to generate initial population with uniform distribution in the solution space. Then, the strategies of repair operator encoding and task priority ordering are designed to achieve tasks-groups-time sequential matching and conflict resolution. Moreover, all individuals are divided into dual-subpopulation by cooperative evolution using the invasive weed optimization algorithm and the Fuch chaotic bat optimization algorithm. Finally, the recombination operator for guiding population evolution is given to balance the exploration and exploitation ability. The simulation example is given to illustrate that the proposed method has better robustness and solving precision for the complicated task allocation scheme.