Building block filtering and fixing

Problems involving high-order building blocks with unknown linkage are difficult to solve. Neither n-point crossover nor uniform crossover can mix high-order building blocks efficiently. A further complication arises when the optimal solution consists of many building blocks. In that case, it is difficult to strike a balance between exploration and exploitation. We have developed a hybrid genetic algorithm, the BBF-GA (building block filtering genetic algorithm), to handle building blocks effectively and efficiently. This GA uses a three-stage approach. During the first stage, a large number of rapidly converging GAs is used to explore the search space. In the second stage, the best individual of each GA is filtered to locate the (potential) building blocks present in this individual. The third stage consists of a GA that exploits these masked individuals by mixing them to obtain the global optimal solution. The BBF-GA performs well on a set of test problems and is able to locate and mix more building blocks than the competitor GAs.