In view of the advantages and disadvantages of artificial bee colony(ABC) algorithm and particle swarm optimization(PSO) algorithm, a hybridization algorithm of Tent chaos artificial bee colony and particle swarm optimization (HTCAP) is proposed. In the HTCAP, an initialization strategy based on Tent chaotic opposition-based learning is applied. All individuals are divided into two sub-swarms by cooperative evolution with Tent chaos artificial bee colony(TCABC) algorithm and Tent chaos particle swarm optimization(TCPSO) algorithm. The best solution obtained by the recombination operator is as the neighbor food source for onlooker bees and the global best of particle swarm, respectively. Simulation results show that, the algorithm not only effectively avoids the premature convergence, but also gets rid of the local minimum. By comparison with the other latest algorithms based on the ABC algorithm and PSO algorithm, the proposed model has better global and local searching abilities.