This repository accompanies Multiple Criteria Decision Making: Methods, Examples and Python Implementations by Jason Papathanasiou and Nikolaos Ploskas (Springer, 2018).
Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research.
https://www.springer.com/us/book/9783319916460
Download the files as a zip using the green button, or clone the repository to your machine using Git.
Release v1.0 corresponds to the code in the published book, without corrections or updates.
For corrections to the content in the published book, see the file errata.md.
See the file Contributing.md for more information on how you can contribute to this repository.