Official implementation of PPSN'24 paper "Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints"

A comprehensive Python implementation of MOEA/D (Multiobjective Evolutionary Algorithm based on Decomposition), a state-of-the-art algorithm for solving multiobjective optimization problems. This implementation is based on the seminal work by Zhang and Li (2007).

MEDEA: A Multi-objective Evolutionary Approach to DNN Hardware Mapping

Multi-objective adversarial perturbations on LiDAR point clouds using NSGA-III to evaluate SLAM robustness. Integrates MOLA SLAM with Isaac Sim via ROS2.

A Julia package for solving multi-objective optimization problems with composite structure (F = f + h). Implements Conditional Gradient, Proximal Gradient, and Partially Derivative-Free algorithms that operate directly on the vector-valued objective, without scalarization or heuristics (direct / vector-optimization methods).

Algorithms for computing or learning equilibria in multi-objective games

Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models

The cMIBACO implementation for lightly robust solutions in MOGenConVRP under uncertainty.

Official Implementation: Boundary Decomposition for Nadir Objective Vector Estimation, NeurIPS 2024; Boundary Decomposition for Finding Nadir Objective Vector in Multi-Objective Discrete Optimization, AAAI 2025.

My Own Hyper-parameter Optimization Toolkit

single & multi objective optimiztion

A Julia wrapper for Bensolve

Multi-Objective Optimization using MOOTLBO algorithm for solving complex optimization problems.

Genetic and evolutionary algorithm implementations in Python

A web application to generate class schedules for ITT students.

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

Code for Paper "Gridless Evolutionary Approach for Line Spectral Estimation With Unknown Model Order"

(Completed) Machine Learning and Multi-Objective Evolutionary Algorithms to Solve Real World Engineering Problems (MultiObjectiveOptimisation and ML)

Benchmark library of vector-valued optimization problems in Julia, with analytic per-objective gradients, filtering functions, and a unified interface for testing and comparisons of multi-objective solvers.

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