Making a Class Schedule Using a Genetic Algorithm with Python
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May 8, 2026 - Python
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Making a Class Schedule Using a Genetic Algorithm with Python
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This repository contains the implementation of an enhanced NSGA-II algorithm for solving the Flexible Job Shop Scheduling Problem (FJSP), focusing on multi-objective optimization. Developed as part of the Bio-Inspired Artificial Intelligence course project at the University of Trento.
A proof-of-concept malware behaviour clustering system backed by a genetic algorithm.
Custom Kubernetes Scheduler using NSGA-III and TOPSIS for Edge Environments
An Evolutionary Scalable Framework for Synthetic Data Generation based in Data Complexity.
An AIOps tool for generating optimized deployment planning reports of distributed analytical pipelines
QUEST: Quantum-inspired Energy-AoI-Aware Task Scheduling in Edge Cloud Continuum
FIRST LEGO League Challenge Scheduler NSGA-III, a python application utilizing Non-dominated Sorting Genetic Algorithm III to schedule FLLC tournaments.
Optimization-Simulation tool for Integrated Water Resource Management. Simulates & optimizes water allocation for irrigation, hydropower, and environmental flows using MOGA.
포켓몬 파티 구성을 퀀트 포트폴리오 최적화로 재해석 — 유전 알고리즘(GA/NSGA-III)으로 최적 전략 조합 탐색
Robust mixed-variable NSGA-III challenger search for less discriminatory tabular models.
Signal processing, ML optimization, and edge computing projects from KETI research (2024.04~2025.09)
A unified multi-objective evolutionary optimization architecture benchmarking NSGA-II, NSGA-III, MOEA/D, and SPEA2 using Hypervolume indicators to resolve WSN spatial constraints.
Multi-agent evolutionary strategy discovery with quality-diversity and NSGA-III search, evaluated against WRDS CRSP equities and Yahoo Finance futures data.
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