ATM Supply Optimizer

A platform aiming to optimize the ATM supply planning for a set of bank ATMs that need to be supplied by a specific provider. The platform is solving the mTSP and CVRP, allowing the user to plan a set of efficient paths in a provided graph.

Installation

Requirements

The following software is required:

• Docker ( optionally )
• Python V3.12
• Pipenv ( if Docker is not used )

Configuration

After downloading the source code from git you will need to configure some parameters in the .env file. The parameters are the following:

• DATASTORE_SUPPLY_INFO : The filepath of the ATM supply info in xlsx format.
• DATASTORE_SUPPLY_TEST_INFO : The filepath of the ATM supply info for evaluation in xlsx format.
• DATASTORE_OUTAGE_INFO : The filepath of the ATM outage info.

If you do install the predictor using Docker then you will need to setup a local MongoDB and provide the following parameters:

• MONGO_USERNAME : The MongoDB username.
• MONGO_PASSWORD : The MongoDB password.
• MONGO_DATABASE : The MongoDB database.
• MONGO_AUTH_DB : The MongoDB authentication database.
• MONGO_HOST : The MongoDB host.
• MONGO_PORT : The MongoDB port.

Docker

The recomented way to install and use ATM_cash_deposit_predictor is through Docker compose. The instruction for installation are the following:

• Download the source code using git.
• Change directory to the root folder of the source.
• Execute the command docker compose up --build -d. It may need sudo rights depending on system setup.
• After the container is running you can either connect to the atmo-python container using the command docker exec -it atmo-python /bin/bash or you can run a command directly using docker exec atmo-python <command>

Pipenv

If Docker is not available or not preferred Pipenv can also be used. The instruction for installation are the following:

• Download the source code using git.
• Change directory to the root folder of the source.
• Execute the command pipenv install --python 3.12.
• After the pipenv is created you can use the pipenv shell using the command pipenv shell and execute the commands normally or execute them using pipenv run <command>.

Usage

The following commands are available:

• python main.py import_data : imports the data from the datastore files and add them to the MongoDB as defined in .env file.
• python main.py create_plans --datafile=”path/to/input/data” --model=ilp : run the prediction model, defined with the --model parameter, on the provided dataset, defined using the --data argument, and print a list of ATMs that will need supply tommorow.
• python main.py evaluate : evaluates the supported models using the test dataset defined in .env and prints various statistics.

Licence

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see https://www.gnu.org/licenses/.