LMEA

Code for paper: Large Language Models as Evolutionary Optimizers

Quick Start

Setup Environment

# clone the repo
git clone https://github.com/cschen1205/LMEA.git

# Go to directory
cd LEMA

# create a new environment and activated it
python -m venv venv
source ./venv/bin/activate

# pyconcorde installation and steup
pip install 'pyconcorde @ git+https://github.com/jvkersch/pyconcorde'

# install dependent pacakges
pip install -r requirements.txt

Setup OpenAI Key

In the src/utils.py file, line 14, place the openai keys in array "open_ai_keys"

# place your openai key in this array. You can put multiple keys if you want to run multiple threads
open_ai_keys = [""]

Dataset

The TSP problems used in experiments of this page are located in Folder data/tsp

Generate TSP problem files

run src/problem.py to generate TSP problems files

python scr/problem.py -name "tsp" -t "rue" -d "tsp" -nc 10,15 -pc 10

Run experiment

You can run the experiment.py python script for experiments. For example:

python src/executor.py -n rue,clu -nc 10,15 -pi 1 -al ec

The above command will run "LLM-EC" experiments on the these problem files:

clu_10_1.tsp (clu type, 10 nodes, 1st problem instance)
clu_15_1.tsp (clu type, 15 nodes, 1st problem instance)
rue_10_1.tsp (rue type, 10 nodes, 1st problem instance)
rue_15_1.tsp (rue type, 15 nodes, 1st problem instance)

The log files of the experiments will be saved in folder "data/logs"

Issues and FAQ

Coming soon!

Plese feel free to contact @cschen if you encounter issues on the project.