Forking Genetic Algorithm with Blocking and Shrinking Modes (fGA)
Shigeyoshi Tsutsui, Yoshiji Fujimoto · international conference on Genetic algorithms · 1993
There are many GA-hard problems that are difficult to solve by the traditional GAs such as problems with multi-modal and deceptive evaluation functions [4] [15]. Many kinds of modified GAs that are aimed to solve these problems are p r o p o s e d s u c h a s C H C [ 2 ] , m G A [ 5 ] , GENITOR[13] and Niche Method[4]. In this paper, we propose a new type of GA, that is, the forking Genetic Algorithm (fGA). The fGA is designed to solve such problems as have multi-modal evaluation functions with many local optimal points. This GA evolves multi-populations. In conventional GAs with multi-populations [1] [6] [10], each population is independently evolved in the same genetic operations. They maintain and enrich diversity gained by genetic drift through immigration of individuals between populations [6] [10]. The distinguishing feature of the fGA is that it has one parent population with a blocking mode and one or more child populations with a shrinking mode as a result of population forking. Each population takes a different role in optimizing tasks. That is, each population is responsible for searching for nonoverlapping sub-areas in the search space. Genetic operators of the fGA, the process of the population forking and empirical results are described in the following sections.