Open source Manufacturing Execution and Performance Monitoring built on Grafana, Influx, and Postgres

MATLAB Tool for Multi-Objective Optimization

CK automation actions to let users implement portable, customizable and reusable program workflows for reproducible, collaborative and multi-objective benchmarking, optimization and SW/HW co-design:

A State Manager focused on KISS and Pareto's Principle

Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.

Finding optimal no of clusters in MOPSO implementation of Wireless Sensor Networks.

Reduce Warehouse Space with the Pareto Principle using Python

Implementation of NSGA-II in Python

Multiple-criteria decision-making (MCDM) with Electre, Promethee, Weighted Sum and Pareto

A Python-based, open source, desktop application to import, read and analyse excel files in order to create and display multiple charts.

Python bindings for OptFrame C++ Functional Core

Advanced choice modeling with multidimensional utility representations.

This is the official repository to PARODIS, the Matlab PAReto Optimal Model Predictive Control framework for DIstributed Systems.

Open Source Javascript library to render screeplots using D3

Source code for the paper "Toward Finding Strong Pareto Optimal Policies in Multi-Agent Reinforcement Learning"

Pareto-related recipes to be used with Plots.jl

Time Series forecasting model for predicting the unit’s movement of the inventory in the warehouses and stores in order to do capacity planning and prepare for peak volume at the granularity level of week/channel/location.

The code in this project solves the problem of finding the optimal diameter for a straight pipe conveying an incompressible fluid, for user defined mass flow rates. The best design solution is considered the one that minimizes both the pressure drop per unitary pipe length and the pipe diameter. Solutions are ranked according to TOPSIS method. The user can input the pipe absolute roughness, to identify the pipe material, and the density and dynamic viscosity, depending from the fluid to be studied.

Build interactive violin plot for Pareto Analysis of your Supply Chain data using Flask and D3.js

No description provided.

Multi-Objective Multi-Agent RL with non-linear utility functions

Pareto (Type I) distribution standard deviation.

Pareto (Type I) distributed pseudorandom numbers.

Create a readable stream for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.

Pareto Simulator

Modeling high dimensional extremes with d-max-decreasing neural networks.

Pareto (Type I) distribution expected value.

Pareto (Type I) distribution variance.

Pareto (Type I) distribution excess kurtosis.

Pareto (Type I) distribution.