Download
JaCoP is a Java Constraint Programming solver. It provides a significant number of (global) constraints to facilitate efficient modeling of combinatorial problems, as well as modular design of search. Documentation is available at project Web site.
Please, note that the sources from version 4.0 are only available at GitHub.
Features
- global constraints
- modular search
License
Affero GNU Public LicenseFollow JaCoP
nel_h2
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
Rate This Project
Login To Rate This Project
User Reviews
-
Thanks for Jacop-solver, it's excellent!
-
Very good Software.
-
JaCoP is very helpful. Its documentation and also the provided samples are a very good introduction to the library. And I liked the way constraints can be composed. http://slowfrog.blogspot.com/2012/02/hexiom-constraints-and-libraries.html
-
I have been using JaCoP in the context of my PhD. JaCoP is very intuitive to use, probably more than Linear Programming solvers. The files are well documented and numerous examples help to understand how to use the existing constraints. I also received feedback from the authors (fast and accurate reply) which helped me to develop new constraints. With that, I not only obtained valuable results for my PhD. I also demonstrated that CP can be used in the context of optical networks, which generated lot of interest in several workshop and conferences. For these reasons and several others (space is missing), I recommend to try JaCoP (as to try it is to love it).
-
I am using JaCoP for my PhD research in the field of digital circuit modeling and automated testware synthesis. It is indeed very simple to integrate and powerful enough in solving complex issues.