Stars
Modeling robust optimization problems in Pyomo
Attention based model for learning to solve different routing problems
Implementation of: Nazari, Mohammadreza, et al. "Deep Reinforcement Learning for Solving the Vehicle Routing Problem." arXiv preprint arXiv:1802.04240 (2018).
[ICML 2023] "Towards Omni-generalizable Neural Methods for Vehicle Routing Problems"
A Python implementation of a lightweight genetic algorithm
TranSPormer: a transformer for the Travelling Salesman Problem
Multi-objective Genetic Programming by NSGA-II in Python
Meta-learning approach for human-interpretable formulas generation
A multi-modal genetic algorithm which will use two niching methods.
ML hyperparameters tuning and features selection, using evolutionary algorithms.
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
The nurse scheduling problem (NSP),is the operations research problem of finding an optimal way to assign nurses to shifts, typically with a set of hard constraints which all valid solutions must f…
Tree Implementation and Methods for Python, integrated with list, dictionary, pandas and polars DataFrame.
A baseline implementation of genetic programming (using trees to encode programs) with some examples of usage.
Repository for PyGEVO, a pythonic framework for Grammatical Evolution
Example code from the book "Deep Learning for the Life Sciences"
Repository to host the GRAPE code developed by the BDS group
Geometric Symmetric Genetic Programming for Symbolic Regression
Master's research
The intent of this challenge is automatic rules induction, i.e. to learn the rules using machine learning, without hand coding heuristics.
The property-based testing library for Python