PLACING ACTUATORS ON SPACE STRUCTURES BY GENETIC ALGORITHMS AND EFFECTIVENESS INDEXES

Genetic algorithms are a powerful tool for the solution of combinatori al problems such as the actuator placement problem. However, they requ ire a large number of analyses with correspondingly high computational costs. Therefore, it is useful to tune the operators and parameters o f the algorithm on simple problems that are similar to more complex an d computationally expensive problems. The present paper employs an eas y-to-calculate measure of actuator effectiveness to evaluate several g enetic algorithms. Additionally, the effects of population size and mu tation rates are also investigated for a problem of placing actuators at 8 of 1507 possible locations. We find that even with the best of th e algorithms and with optimum mutation rates, tens of thousands of ana lyses are required for obtaining near optimum locations. We propose a procedure that estimates the effectiveness of the various locations an d discards ineffective ones, and find it helpful for reducing the cost of the genetic optimization.