An Improved Artificial Fish Swarm Algorithm and Application

An improved Artificial Fish Swarm Algorithm (AFSA) based on Hooke-Jeeves (HJ) algorithm is proposed and improved AFSA is applied to design lamps of changeable color temperature and high luminous efficacy in this paper. The disadvantage of AFSA stochastic moving without a definite purpose is improved by HJ algorithm, owing to HJ’s great ability of local searching. Accuracy of solution is improved by the adaptive weight. The improved AFSA is verified through an example of how to search for the most luminous efficacy of LED mixing color. The white, red, green and blue LEDs are chosen to design LED lamp samples. LED proportions of 5000K color temperature among those LEDs are optimized by AFSA and new AFSA in the Matlab. The obtained results indicate that improved AFSA is faster and higher accuracy. After LED lamps are tested by integrating sphere, the results show that the difference between the actual value and simulation calculation value is tiny, the new AFSA is effective. The improved AFSA provides a new efficient calculation method of LED proportions. Compared with the traditional manual calculation LED proportions, new method not only saves a significant amount of time, but also achieves higher luminous efficacy for lamps. All this shows that the new method is effective and has high practical value.