Seeding-inspired chemotaxis genetic algorithm for the inference of biological systems
A new seeding-inspired chemotaxis genetic algorithm (SCGA) is proposed. SCGA successfully identified a thirty-gene 1800-connection system by only three steps. A good initial start and a restricted search space are not necessary. Seeding-inspired genetic operations largely improve population competition. Winner-chemotaxis-induced population migration overcomes GAs weakness.
reverse engineering s-system modeling memetic algorithm structure identification evolutionary algorithm