Evolutionary computation 1960s-1970s
A series of optimization algorithms based on biological evolution principles have been proposed, such as evolutionary strategies and evolutionary programming. These algorithms attempt to simulate the evolutionary process in nature to solve practical problems. The motivation for researchers to propose these algorithms is that the biological evolution process has a powerful global search capability and is expected to provide an effective method for solving complex optimization problems.
Ingo Rechenberg and Hans-Paul Schwefel proposed lithuania mobile database evolution strategies, an evolutionary algorithm based on real number coding. Evolution strategies are mainly used for continuous optimization problems. Similar to genetic algorithms, evolution strategies also have the limitations of slow convergence and sensitive parameter settings. In 1973, Rechenberg published a book titled "Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipien der biologischen Evolution", which detailed the principles and implementation methods of evolution strategies.
Evolutionary programming 1970s
David E. Goldberg proposed evolutionary programming, an optimization method based on simulating evolutionary processes, for solving discrete optimization problems. The limitations of evolutionary programming are similar to those of genetic algorithms and evolutionary strategies, mainly manifested in slow convergence and sensitive parameter settings. In 1989, Goldberg published a book titled "Genetic Algorithms in Search, Optimization, and Machine Learning", which detailed the principles and implementation methods of evolutionary programming.