Name		Name	Last commit message	Last commit date
Latest commit History 37 Commits
Data		Data
HybridGA		HybridGA
NSGA		NSGA
Outputs		Outputs
Prepro		Prepro
configs		configs
plan		plan
.gitignore		.gitignore
README.md		README.md
ablation_study.py		ablation_study.py
analysis.ipynb		analysis.ipynb
config.json		config.json
hyper_parameter_tuning.py		hyper_parameter_tuning.py
main.py		main.py
single_objective.py		single_objective.py
testing.py		testing.py

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Meal-Planning

My BTech Term Project (BTP) at IIT Kharagpur

Refer to the BTP Report and my Final Presentation for details.

A compilation of the slides presented almost every week during the project: here

Required Libraries

Sklearn, scipy, Gensim, Numpy, Pandas, Networkx, Tqdm

How to Run

Install the required libraries
Update the config.json file. A standard one has been provided
Run the main file python3 main.py

Code Structure

main.py: The file that needs to be run. Loads the config from the config.json file.
hyper_parameter_tuning.py: Contains code to perform a grid search for the best hyper-parameters for the GA
testing.py: The code for testing the pipeline for a variety of constraints
Configs: various configs that are used for testing the model for a variety of constraints and preferences.
Data: Dataset files. For more details refere here
Hybrid GA: Contains the code for Evolution according to Hybrid GA algorithm, the Hybrid GA Population maintatining separate lists for feasible and infeasible solutions and Utility files for Hybrid GA.
NSGA: Contains the code for Evolution according to NSGA 2 algorithm, the standard GA population and utility files
plan: Contains code for the meal planner. Details here
Outputs Some output logs that contain suggested meal plans
Prepro:
- Contains code for preprocessing the dataset. The Data folder contains the preprocessed files