<p>I'm studying the <a href="https://arxiv.org/abs/0903.0544" rel="nofollow noreferrer">Moser-Tardos algorithm</a>, which is often used to efficiently find solutions to satisfiability problems and avoid bad events in probabilistic settings. I’ve read that it’s mainly applied in theoretical computer science, particularly for SAT problems, random constraint satisfaction, and graph theory.</p>
<p><a href="https://i.sstatic.net/rUCX2ihk.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/rUCX2ihk.png" alt="enter image description here" /></a></p>
<p>Event <span class="math-container">$A_i$</span>​ represents a bad event.</p>
<p>Given its theoretical power, my question is: <strong>Are there any known cases where the Moser-Tardos algorithm (or its variants) has been applied to solve real-world, practical problems?</strong> For example, has it been used in areas like software engineering, logistics, or industry-specific optimizations?</p>
<p>I understand that the Moser-Tardos algorithm works by resampling entire clauses, whereas many heuristic SAT solvers tend to flip only a single variable. <strong>Given this difference, has the Moser-Tardos algorithm been practically applied in any real-world SAT solving scenarios?</strong></p>
<p>I'd love to learn about any examples, papers, or projects that showcase its real-world use. Thanks in advance!</p>

CC BY-SA 4.0
2024-10-17T08:54:59.260Z
@EmilJeřábek $A_i$  represents a bad event. Thank you for your insight, I should have clarified that.
Jxb
CC BY-SA 4.0
2024-10-17T23:56:36.223Z
Yes, in generating combinatorial arrays for testing interactions in large-scale software systems (this is my research area).
Ryan Dougherty
CC BY-SA 4.0
2024-10-18T01:30:34.647Z
@RyanDougherty Thank you for your reply! Could you kindly provide some papers or resources related to this topic? I would really appreciate it because I’m not very familiar with this area.
Jxb
CC BY-SA 4.0
2024-10-21T01:20:16.197Z
see for example this paper by Sarkar/Colbourn in section 5: https://arxiv.org/pdf/1606.06730. It has experiments to generate an initial array randomly of size guaranteed by the LLL.
Ryan Dougherty
<reference-request><sat><application-of-theory>
Has the Moser-Tardos Algorithm Been Applied to Real-World Problems?
Jxb
# Has the Moser-Tardos Algorithm Been Applied to Real-World Problems?

(Asked by: username_0 on 2024-10-17)

I'm studying the [Moser-Tardos algorithm](https://arxiv.org/abs/0903.0544), which is often used to efficiently find solutions to satisfiability problems and avoid bad events in probabilistic settings. I’ve read that it’s mainly applied in theoretical computer science, particularly for SAT problems, random constraint satisfaction, and graph theory.

[![enter image description here](https://i.sstatic.net/rUCX2ihk.png)](https://i.sstatic.net/rUCX2ihk.png)

Event $A\_i$​ represents a bad event.

Given its theoretical power, my question is: **Are there any known cases where the Moser-Tardos algorithm (or its variants) has been applied to solve real-world, practical problems?** For example, has it been used in areas like software engineering, logistics, or industry-specific optimizations?

I understand that the Moser-Tardos algorithm works by resampling entire clauses, whereas many heuristic SAT solvers tend to flip only a single variable. **Given this difference, has the Moser-Tardos algorithm been practically applied in any real-world SAT solving scenarios?**

I'd love to learn about any examples, papers, or projects that showcase its real-world use. Thanks in advance!

**Tags:** reference-request, sat, application-of-theory
> **Comments:**
> **username_0**: @EmilJeřábek $A_i$  represents a bad event. Thank you for your insight, I should have clarified that.  
> **username_1**: Yes, in generating combinatorial arrays for testing interactions in large-scale software systems (this is my research area).  
> **username_0**: @RyanDougherty Thank you for your reply! Could you kindly provide some papers or resources related to this topic? I would really appreciate it because I’m not very familiar with this area.  
> **username_1**: see for example this paper by Sarkar/Colbourn in section 5: https://arxiv.org/pdf/1606.06730. It has experiments to generate an initial array randomly of size guaranteed by the LLL.  

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## 0 answers

