Gigs with Guarantees: Achieving Fair Wage for Food Delivery Workers

This repository contains official implementation of the algorithms defined in our paper.

Getting Started

These instructions will get you a copy of the project up and running on your local machine.

Prerequisites

The algorithms are implemented in C++11 (GCC 7.4.0), and GPR training and evaluation scripts are implemented in Python 3 (Python 3.6.9)

Installation

Setup a conda environment which includes packages required to run evaluation scripts:

conda env create -f environment.yml
conda activate w4f_evn

Datasets and evaluation procedure

The code for simulation and algorithms defined in our paper is provided in [./code]. An anonymized version of the proprietary dataset will be made available once an agreement is signed. Instructions to request data are available at this link.

References

[1] M. Joshi, A. Singh, S. Ranu, A. Bagchi, P. Karia, and P. Kala,“Batching and matching for food delivery in dynamic road networks,”inProc. ICDE, 2021.
[2] Anjali and Rahul Yadav and Ashish Nair and Abhijnan Chkraborty and Sayan Ranu and Amitabha Bagchi, "FairFoody: Bringing in Fairness in Food Delivery," inProc. AAAI, 2022.
[3] https://github.com/idea-iitd/FoodMatch
[4] https://github.com/idea-iitd/fairfoody