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This paper introduces a new general framework for genetic algorithms to solve a broad range of optimization problems. When designing a genetic algorithm, there may be several alternatives for a component such as crossover, mutation or decoding procedure, and it may be difficult to determine the...
Persistent link: https://www.econbiz.de/10011558747
This paper introduces a new general framework for genetic algorithms to solve a broad range of optimization problems. When designing a genetic algorithm, there may be several alternatives for a component such as crossover, mutation or decoding procedure, and it may be difficult to determine the...
Persistent link: https://www.econbiz.de/10011734932