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I use pyinstaller to generate an executable code for the example in the Getting Started section successfully. However, when I run the code, I get an error:
`import autograd.numpy as anp
import numpy…
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Dear beloved OpenMole developers,
I'm discovering the implementation of NSGA2 in OpenMole. Sometimes my task fails on some specific combinations of input values, which makes sense, as the simulatio…
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Hi there,
I was just wondering how to use the experimenter using ones own problem rather than a predefined problem?
# Run the algorithm
N = 2000
problem = Problem(multiple_days_assigned_size,…
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Hi,
While trying to run use MOEAD algorithm for optimization, I am facing the following issue:
- The number of solutions that are evaluated after first generation reduces to 1.
The issue…
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I only found "selection=TournamentSelection(func_comp=comp_by_cv_then_random)" in nsga3.py. But I didn't find code about addition of new reference points and deletion of existing reference points,whic…
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Sorry to interrupt, I'm debugging nsga3 multi-target evolution, I need to get 200 parameters to weight and remove some unimportant parameters, but I found that the nsga3 output is linear, not obviousl…
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```
class NSGA3(GeneticAlgorithm):
def __init__(self,
ref_dirs,
pop_size=None,
sampling=IntegerFromFloatSampling(clazz=FloatRandomSampling…
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I am curious if there's a way to provide initial input values to the algorithm so that the search would be quicker?
I am not quite familiar with those genetic algorithms, correct me if I am wrong …
hyumo updated
4 years ago
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### Scenario:
1. 混合编码
2. 使用过的模板soea_psy_XXX_templet.py
3. version: geatpy-2.4.1
---
### 错误复现
以`geatpy/geatpy/demo/soea_demo/soea_demo5/MyProblem.py/ `这个demo为例,当混合编码决策变量个数为4个,取值范围为[1, 7],也就是demo里…
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pop = self.pop[I]
print(pop.shape)
print(self.pop.get("is_closest"))
if len(pop) == 1:
self.opt = pop
else:
self.opt = pop[self.po…