A Machine Learning and Optimization framework for Objective-C and Swift (MacOS and iOS)

Multi-objective Optimization of Apache Spark in Geo-distributed Datacenters

My Own Hyper-parameter Optimization Toolkit

Multi-objective Bayesian optimisation framework.

Python Multi-Objective Simulation Optimization: a package for using, implementing, and testing simulation optimization algorithms.

A web application to generate class schedules for ITT students.

Code for "A Multi-Objective Test Selection Tool using Test Suite Diagnosability"

A rational and extensible algorithm for solving multi-objective optimization problems

Multi-Objective Design using Sequential Quadratic programming

[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control

The W-Model, a tunable Black-Box Discrete Optimization Benchmarking (BB-DOB) problem, implemented for the BB-DOB@GECCO Workshop.

Discrete-world as the name says

Bayesian Optimization and Uncertainty Analyses Tools

PDF's of all of my current publications.

All accepted papers for the Multi-Objective Decision Making Workshop 2021.

An algorithm to calculate all pure strategy Nash equilibria in multi-objective games with quasiconvex utility functions

Paxplot is a Python visualization library for parallel coordinate plots based on matplotlib.

A lean little learning library, in LUA.

MOEA/D is a general-purpose algorithm framework. It decomposes a multi-objective optimization problem into a number of single-objective optimization sub-problems and then uses a search heuristic to optimize these sub-problems simultaneously and cooperatively.