[Regression] Index matching is wrong for dataframe operations such as div and mul
#### Code Sample, a copy-pastable example if possible
```python
import pandas as pd
categories = ['B', 'A', 'C']

a = pd.DataFrame({'x':categories})
a['y'] = 1
a['value'] = 1
a['x'] = a['x'].astype('category')

# the sort_values is important here to trigger the bug
b = a.copy().sort_values('x')
a['x'] = a['x'].cat.set_categories(categories)
print(a['x'])
print(b['x'])

a = a.set_index(['x', 'y'], )['value']
b = b.set_index(['x', 'y'], )['value']
a.mul(b)
```
#### Problem description

In pandas 1.01+ the result of running the above code is wrong, where it returns the correct result in 0.25.3

The output of the above in 1.0.5 gives two NaN values with duplicate index entry:
![image](https://user-images.githubusercontent.com/7702207/87791831-3d98a780-c843-11ea-8ad1-e5fc6e7d6bd6.png)

It is triggered with the following conditions:
- having a multi-index
- a difference in the order of the categories in the index (using the set_categories)
- a difference in order of the index itself (using the sort_values)

#### Expected Output
The expected output is returned in 0.25.3:
![image](https://user-images.githubusercontent.com/7702207/87791732-12ae5380-c843-11ea-9d86-cd47384b1ab0.png)

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None

pandas           : 1.0.5
numpy            : 1.18.5
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 46.1.3.post20200325
Cython           : 0.29.16
pytest           : 5.4.1
hypothesis       : 5.19.3
sphinx           : 3.1.2
blosc            : None
feather          : None
xlsxwriter       : 1.2.9
lxml.etree       : 4.5.2
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : 4.9.1
bottleneck       : 1.3.2
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.5.2
matplotlib       : 3.2.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.4
pandas_gbq       : None
pyarrow          : 0.16.0
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.18
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.2.9
numba            : 0.50.1
</details>
