According to the constrained length of the bars,the unconstrained optimization model is constructed to formulate the forward position analysis for a 6 degrees-of-freedom general 6-SPS parallel mechanism,and the differential evolution（ DE） algorithm is employed to solve this problem. Aiming at the basic DE algorithm has some weaknesses,such as evolutionary stagnation and falling into local extremum domains,an adaptive strategy for introducing new individuals is presented to improve its optimization performance. This strategy is dynamically incorporated into DE algorithm to form an adaptive DE（ ADE） algorithm,which adopts hybrid mutant operators,and scale and cross factors with trigonometric function perturbations. The numerical results of the forward kinematic analysis for a general 6-SPS parallel mechanism show that ADE algorithm can obtain all high accuracy solutions with lighter computational cost. Furthermore,the ADE algorithm is compared with basic DE,the adaptive mutation particle swarm optimization,and improved artificial bee colony algorithms,and it is verified that the former outperforms the compared algorithms in term of convergence precision and calculated robustness.