The invention discloses an improved hybrid chimpanzee optimization algorithm, and the method comprises the steps: employing a chimpanzee algorithm to carry out the initialization of a population through employing a good point set, balancing the global search capability and local development capability of the algorithm based on a nonlinear convergence factor of a tangent function, and employing a flip foraging strategy at a position updating part. According to the improved hybrid chimpanzee optimization algorithm (DFSChOA) provided by the invention, population initialization is performed by using a good point set, the diversity of population individuals is improved, a foundation is laid for global optimization, and a given convergence factor based on a tangent function factor is used for balancing the search capability and the development capability of the algorithm; and a prying foraging strategy is provided at a position-changing position, so that the possibility that the algorithm falls into local optimum is improved.