This archive is distributed in association with the INFORMS Journal on Computing under the MIT License.
The software and data in this repository are a snapshot of the software and data that were used in the research reported in the paper A Computational Study of the Tool Replacement Problem by Yuzhuo Qiu, Mikhail Cherniavskii, Boris Goldengorin, Panos M. Pardalos.
To cite the contents of this repository, please cite both the paper and this repo, using their respective DOIs.
https://doi.org/10.1287/ijoc.2023.0474
https://doi.org/10.1287/ijoc.2023.0474.cd
Below is the BibTex for citing this snapshot of the repository.
@misc{ToolReplacementProblem,
author = {Yuzhuo Qiu, Mikhail Cherniavskii, Boris Goldengorin, Panos M. Pardalos},
publisher = {INFORMS Journal on Computing},
title = {A Computational Study of the Tool Replacement Problem},
year = {2023},
doi = {10.1287/ijoc.2023.0474.cd},
note = {Available for download at https://github.com/INFORMSJoC/2023.0474},
}
This software aims to compare IGA, IGA-bit, IGA-full and KTNS algorithms for the Tool Replacement Problem. The experiments were conducted on a server running a 64-bit Windows 10 operating system, equipped with Intel(R) Core i5 CPU 2.6 GHz and 4 GB of RAM. To compare the algorithms for each of the 10 problem instances of data sets from Catanzaro et al. we generate 105 job sequences. Additionally, for each of the 5 problem instances of data sets from Mecler et al. we generate 2·105 job sequences.
- src/main.cpp contains the algorithms and experiments implemented in C++.
- scripts/tests.py еxecutes src/main.cpp and plots a graph to present the performance for outcome of the experiments.
Figure 8 in the paper shows the results of the Comparison of KTNS and IGA algorithms for Catanzaro et al. and Mecler et al. datasets.
In Linux, to replicate the results do
make all