A framework for single/multi-objective optimization with metaheuristics

NSGA-Net, a Neural Architecture Search Algorithm

A Python implementation of the decomposition based multi-objective evolutionary algorithm (MOEA/D)

🧬 Modularised Evolutionary Algorithms For Python with Optional JIT and Multiprocessing (Ray) support. Inspired by PyTorch Lightning

hybrid genetic algorithm for container loading problem

Making a Class Schedule Using a Genetic Algorithm with Python

🎓An AI tool to assist universities with optimal allocation of students to supervisors for their dissertations. Devised a multi-objective genetic algorithm for the task.

Contains python code of an NSGA-II based solver with multiple genetic operator choices for the multiple travelling salesman problem with two objectives. Also contains sample instances from TSPLIB. (Deliverable for the ECE 750 AL: Bio & Comp Fall 2021 individual project @ UWaterloo)

Implementation of NSGA-II in Python

The NSGA-II for the multi-objective shortest path problem

NSGA-II implemetation for the elaboration included the research paper entitled "Multi-objective Optimization for Virtual Machine Allocation and Replica Placement in Virtualized Hadoop Architecture"

Python bindings for OptFrame C++ Functional Core

A stochastic circuit optimizer for Cadence Virtuoso, using the NSGA-II genetic algorithm.

The multiobjective evolutionary algorithm NSGA-II implemented by Python.

Multi-objective Flexible Job Shop Scheduling Problem with transportation constraint solved with NSGA-II, VNS and improved initialisation

A python implementation of NSGA-II multi-objective optimization algorithm.

A Memetic Procedure for Global Multi-Objective Optimization

[ICONIP 2021] "Training-Free Multi-Objective Evolutionary Neural Architecture Search via Neural Tangent Kernel and Number of Linear Regions" by Tu Do, Ngoc Hoang Luong

Portfolio Optimization Using Evolutionary Algorithms

Motif discovery for DNA sequences using multiobjective optimization and genetic programming.