Electronic Circuit Optimization Design Algorithm based on Adaptive Culture Search

Electronic circuit optimization design is important research field in engineering applications. Circuit scale and the time of evaluate the circuit are the challenge problems for circuit optimization design algorithm and the traditional optimization algorithms cannot solve the two problems very well. Cultural Algorithms are a class of computational models derived from observing the cultural evolution process in nature. Aiming at the disadvantages of basic Cultural Algorithms like being trapped easily into a local optimum, this paper improves the basic Cultural Algorithms and proposes the improved cultural algorithm (ICA) to solve the overcomes of the basic Cultural Algorithms. The new algorithm keeps not only the fast convergence speed characteristic of basic Cultural Algorithms, but effectively improves the capability of global searching as well. For the case studies, the new algorithm means has proved to be efficient and the experiment results show that the new means have got the better results.