I m试图利用遗传学算法(使用python 3.x)解决等距系统。 是否采用PyGAD模块或提高大会产出准确性的方法进行多目标分析?
From version 3.2 PyGAD is supporting multi-objective optimization. Citing documentation:
把这个问题视为多目标,只是回到一个清单、图谋或假设。 脱离健身功能。
Example of code from documentation:
def fitness_func(ga_instance, solution, solution_idx):
output1 = numpy.sum(solution*function_inputs1)
output2 = numpy.sum(solution*function_inputs2)
fitness1 = 1.0 / (numpy.abs(output1 - desired_output1) + 0.000001)
fitness2 = 1.0 / (numpy.abs(output2 - desired_output2) + 0.000001)
return [fitness1, fitness2]
千年大会并不支持现阶段的多目标优化。 只有单一目标优化得到支持。
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