The approach involves the usage of Multi-Criteria Decision Analyses, including Weighted Sum Model (WSM), Weighted Product Model (WPM) and Topsis to produce ranking of decisions on incomplete structured datasets. Subsequently, Multi-variate Regression, Deep Neural Network (DNN) and a Multi-layer Perceptron (MLP) are trained to predict such rankings.

This repository contains Python implementations of various Multi-Criteria Decision Making (MCDM) methods. These techniques help in evaluating and ranking alternatives based on multiple criteria, often used in decision analysis and optimization problems.

EOS is a set of functions (intended to be a package) that encompases everything within a centralized Earth Observation Satellite scheduling system in terms of Scenario generation, problem setup, solution approach, decision maker preference integration.

The RMCDA package is a comprehensive toolkit for Multi-Criteria Decision Analysis (MCDA), designed to facilitate the evaluation and ranking of alternatives based on multiple criteria. The package provides methods for implementing various MCDA techniques, including pairwise comparisons, partial-order analysis, and dominance-based decision rules.

A Configuration of Some Soft Decision-Making Algorithms via fpfs-matrices

Applying Dynamic Programming on Multi-Criteria Knapsack Problem with 2 constraints

Multi-Criteria Decision solving techniques Algorithms to solve complex decision-making problems influenced by multiple criteria. We will discuss why we need such techniques and explore available algorithms in the cool skcriteria python package

Multi-Method MCDM/MCDA Software. To cite this software publication: https://link.springer.com/article/10.1007/s10668-023-03349-z Download ka-decision.exe for Windows: https://github.com/kadirkirda/ka-decision/raw/refs/heads/main/software/ka-decision.exe

⚖️ Multi-criteria decision-making methods

Multi-Objective Optimization and Multi-criteria Decision Making

A multi-criteria decision analysis (MCDA)-based composite proxy target variable generation technique for business decision modeling that uses relevant features or independent variables conceptually related to the intended target variable.

A Review on Some Soft Decision-Making Methods

Java framework for Evolutionary Computation and Decision Making (JECDM). It is a computational framework written in Java that primarily intends to facilitate research on preference-based evolutionary multi-objective optimization.

Multi-criteria optimization using multimethod adaptive search in MATLAB and Python

A New Approach to Group Decision-Making Method Based on TOPSIS Under Fuzzy Soft Environment

Prevalence Effect Method

End-to-End Python implementation of the Heuristic-Augmented Financial Risk Index (HAFRI) framework from Abdullah et al. (2025). Processes expert surveys and financial statements to generate composite risk scores, enabling robust ranking of fiscal periods through hierarchical decomposition and consistency validation.

Web application for selecting mining methods based on geological parameters, using methodologies like Nicholas 1981, 1992, UBC, and Sh&B. Supports quick technical and economic evaluations with geomechanical classification tools. Built with JavaScript, HTML5, and CSS3, without frameworks.

MCDM using TOPSIS: A technique for multi-criteria decision making, utilizing the TOPSIS method to evaluate alternatives based on multiple criteria.

基于层次分析法（AHP）的优秀党员评价系统，以Excel表格实现

Multi-criteria decision-making API for calculating evaluation criteria weights using AHP and Best-Worst Method, developed with FastAPI and Python.

Identifier Of Solutions Of Interest

Analytical Hierarchy Process Decision Tool is a web-based tool designed to facilitate decision-making across various domains using the Analytical Hierarchy Process (AHP). It allows users to define criteria and alternatives, perform pairwise comparisons with intuitive slider controls, and generate priority vectors for robust evaluation of options.

Multiple criteria sorting and decision making using Assess method.

Global city scoring and exploration tool designed to help users compare and discover cities that best match their moving priorities. Built with Python, Streamlit, Folium, and Pandas, this app combines open public datasets with weighted multi-factor scoring to provide interactive decision support for relocation planning.

Analytical Hierarchy Process app for Multi Criterion Decision Making