The invention provides an artificial fish-swarm algorithm based on overall information, comprising the followings steps: (1) firstly initializing settings, (2) calculating the fitness value of each artificial fish and recording the status of overall optimized artificial fish, (3) evaluating each artificial fish and selecting the behaviors to be acted by fish, including feeding, bunching, tailing, biting and jumping, (4) acting the behaviors selected by the artificial fish and updating the position information of the fish based on the overall and local information, (5) updating the status of overall optimized artificial fish, and (6) outputting the result if the condition of loop termination is met, or returning to the step (2). The invention improves the basic artificial fish-swarm algorithm and provides a new fish-swarm optimizing mode and biting and jumping behaviors of the artificial fish, reduces the complexity the algorithm enhances the overall optimizing capability of algorithm and increases the speed and precision of convergence of the algorithm.