Data and R scripts for the Case Study of the Paper "Unmanned Aerial Vehicle Information Collection Missions with Uncertain Characteristics"
This archive is distributed in association with the INFORMS Journal on Computing under the MIT License.
The R scripts and data in this repository are a snapshot of the scripts and data that were used in the case study reported on in the paper Unmanned Aerial Vehicle Information Collection Missions with Uncertain Characteristics by M.D. Moskal, E. Dasdemir and R. Batta.
To cite this material, please cite the paper and the code using its DOI: https://doi.org/10.1287/ijoc.2022.1245.cd
Below is the BibTex for citing this version of the code.
@article{Moskal2022UAV,
author = {Michael D. Moskal, Erdi Dasdemir, Rajan Batta},
publisher = {INFORMS Journal on Computing},
title = {R Scripts for Unmanned Aerial Vehicle Information Collection Missions with Uncertain Characteristic}
year = {2022},
doi = {10.1287/ijoc.2022.1245.cd},
url = {https://github.com/INFORMSJoC/2022.0032},
}
The goal of this repository is to share data and R scripts of the case study of our paper. Our motivation is to present our code and results in a reproducible way and facilitate the coding effort of those who want to run further experiments or improve our model.
We have a simple repository structure.
- data and scripts folder contains two subfolders for the civilian and military case applications. Each subfolder contains the input data in text files and the corresponding R script. There is also an additional spreadsheet (.xlsx file) in the main folder with raw data to make it easier to understand the data. Note that Each R script reads the data from the input text files in the same location. Please set the working directory accordingly at the first lines of the scripts.
We adapt the data set provided by Dasdemir et al. (2022) to create the problem instances for civilian and military applications. This data set includes the elevation and coordinate data of 58 fourteeners, and the water capacity, elevation, and coordinate data of 41 water reservoirs from the State of Colorado. Please see data_and_scripts folder and spreadsheet file to view the data.
R scripts employ Gurobi solver to solve the mathematical optimization models. To run the scripts, you should first install Gurobi on your computer and then the Gurobi R package to your R insallation.
- Please visit Gurobi web page for installing Gurobi and obtaining a license.
- Please visit Gurobi R Installation Guide and Installing the R Package pages to use Gurobi on R.
For support in using the scripts and data you can reach the authors by email erdidasdemir@gmail.com.