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[NeurIPS 2024] ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution

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How to run with langflow

Install container for docker

Download image

docker pull langflowai/langflow:v1.1.0

Install container

docker create --name langflow-reevo -p 7860:7860 langflowai/langflow:v1.1.0

Import demo flow graph using import function in langflow UI and import langflow_json\TinhToanTienHoaDemo.json file

Connect and run

Clone this repo

git clone https://github.com/hotamago/reevo.git

Example command

python main.py problem=tsp_aco init_pop_size=30 pop_size=10 max_fe=100 timeout=10 algorithm=hota llm_client=langflow llm_client.api_url="http://localhost:7860" llm_client.flow_id="d240dea0-b62d-488b-8866-4a1d13c7d9d7"

Explain:

  • problem = name of problem to solve (check name in problems folder)
  • init_pop_size = initial population size
  • pop_size = population size
  • max_fe = maximum function evaluations
  • timeout = timeout in seconds
  • algorithm = algorithm to use (e.g., hota, reevo)
  • llm_client = language model client (e.g., langflow, openai)
  • llm_client.api_url = API URL of langflow
  • llm_client.flow_id = flow ID in langflow

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