JaCoP4.8 - Download
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Publisher Description
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.
- global constraints
- modular search
About JaCoP
This Computer program is available in English. It was last updated on 13 October, 2026. JaCoP is compatible with the following operating systems: Linux, Mac, Windows.
The company that develops JaCoP is krzku. The latest version released by its developer is 4.8.
The download we have available for JaCoP has a file size of 2.1 MB. Just click the green Download button above to start the downloading process. The program is listed on our website since 2020-11-24 and was downloaded 0 times. We have already checked if the download link is safe, however for your own protection we recommend that you scan the downloaded software with your antivirus. Your antivirus may detect the JaCoP as malware if the download link is broken.
How to install JaCoP on your Windows device:
- Click on the Download button on our website. This will start the download from the website of the developer.
- Once the JaCoP is downloaded click on it to start the setup process (assuming you are on a desktop computer).
- When the installation is finished you should be able to see and run the program.
Version History
version 4.8
posted on 2020-11-24
version JaCoP-3.1
posted on 2011-02-04
Several fixes and updates
Disclaimer
External Download
We do not host JaCoP on our servers. We did not scan it for viruses, adware, spyware or other type of malware. This app is hosted by the software publisher and passed their terms and conditions to be listed there. We recommend caution when installing it.
The external download link for JaCoP is provided to you by apps112.com without any warranties, representations or guarantees of any kind, so access it at your own risk.
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