SDMP is an optimization software package for solving sequential decision problems using approximate dynamic programming.
SDMP is licensed under the MPL 2.0 license.
You can find the documentation at
English (ENG): https://swonh.gitbook.io/sdmp-user-manual-eng/
Korean (KOR): https://swonh.gitbook.io/sdmp-user-manual-kor/
OS: Windows 10 or higher
IDE: Visual Studio 2019 or higher
To use SDMP, you must first install it.
Download latest version: SDMP-2.0.1-win64.zip
Note Run the Install.bat file, and it will install automatically. (Do not run any other files.)
If you need help, please open a GitHub issue.
We welcome collaborators! If you want to work with us to improve and expand our software, please contact us! (You can also submit a pull request directly.)
Contact: swonhong.github@gmail.com
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korean Government under Grant 2021R1A2C2005531 (PI: Kyungsik Lee).
Related Publication:
An Approximate Dynamic Programming Approach to Wafer-Lot Scheduling for Parallel Multi-Chamber Equipment in Semiconductor Fabrication Lines
Sungwon Hong, Younsoo Lee, Kyungsik Lee
International Journal of Production Research, 2025.
10.1080/00207543.2025.2584726
New Integer Optimization Models and an Approximate Dynamic Programming Algorithm for the Lot-sizing and Scheduling Problem with Sequence-dependent Setups
Younsoo Lee, Kyungsik Lee
European Journal of Operational Research, 302(1), 230-243, 2022.
10.1016/j.ejor.2021.12.032
Accelerated Dynamic Programming Algorithms for a Car Resequencing Problem in Automotive Paint Shops
Sungwon Hong, Jinyoung Choi, Jinil Han, Kyungsik Lee
Applied Mathematical Modeling, 64, 285–297, 2018.
10.1016/j.apm.2018.07.035