Metadata-Version: 2.1
Name: objective-weights-mcda
Version: 0.0.9
Summary: Package for Multi-Criteria Decision Analysis with Objective Criteria Weighting
Home-page: https://github.com/energyinpython/objective-weights-for-mcda
Author: Aleksandra Bączkiewicz
Author-email: aleksandra.baczkiewicz@phd.usz.edu.pl
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.4
Description-Content-Type: text/markdown
License-File: LICENSE

# objective-weights-for-mcda

This is Python 3 library dedicated for multi-criteria decision analysis with criteria weights determined by objective weighting methods.
The documentation is provided [here](https://objective-weights-for-mcda.readthedocs.io/en/latest/)

# Installation
Downloading and installation of `objective-weights-mcda` package can be done with using pip

```
pip install objective-weights-mcda
```

# Methods
`mcda_methods` includes:
- `vikor` with VIKOR method

Other modules include:
- `additions` include `rank_preference` method for ranking alternatives according to MCDA score

- `correlations` include: 
	- Spearman rank correlation coefficient `spearman`, 
	- Weighted Spearman rank correlation coefficient `weighted_spearman`,
	- Pearson correlation coefficient `pearson_coeff`
	
- `normalizations` with methods for decision matrix normalization:
	- `linear_normalization` - Linear normalization,
	- `minmax_normalization` - Minimum- Maximum normalization,
	- `max_normalization` - Maximum normalization,
	- `sum_normalization` - Sum normalization,
	- `vector_normalization` - Vector normalization
	
- `weighting_methods` include 11 objective weighting methods for determination of criteria weights (significance) without decision-maker involvement:
	- `equal_weighting` - Equal weighting method
	- `entropy_weighting` - Entropy weighting method
	- `std_weighting` - Standard deviation weighting method
	- `critic_weighting` - CRITIC weighting method
	- `gini_weighting` - Gini coefficient-based weighting method
	- `merec_weighting` - MEREC weighting method
	- `stat_var_weighting` - Statistical variance weighting method
	- `cilos_weighting` - CILOS weighting method
	- `idocriw_weighting` - IDOCRIW weighting method
	- `angle_weighting` - Angle weighting method
	- `coeff_var_weighting` - Coefficient of variation weighting method
	
Examples of usage of `objective_weights_mcda` are provided on [GitHub](https://github.com/energyinpython/objective-weights-for-mcda) in [examples](https://github.com/energyinpython/objective-weights-for-mcda/tree/main/examples)

## License
This package called `objective-weights-mcda` was created by Aleksandra Bączkiewicz. It is licensed under the terms of the MIT license.

## Note
This project is under active development.


