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CMPL (Coliop/Coin Mathematical Programming Language) is a modeling language and solving system for mathematical programming and linear optimization problems. It aims to strike a balance between the clarity of mathematical model expression and the flexibility of a programming language. Coliop is the integrated development environment included in the CMPL distribution package; both are GPLv3 open-source projects.
In terms of functionality, CMPL can pass model instances to solvers such as HiGHS, SCIP, CBC, GLPK, Gurobi, and CPLEX, with HiGHS and SCIP included in the standard package. It also supports converting problems to MPS or Free-MPS, making it easier to connect with other solvers. The platform covers Windows, OS X, Linux, and Raspbian, making it suitable for both desktop and server environments.
CMPL includes pyCMPL, jCMPL, and CMPLServer. pyCMPL is a Python API and interactive shell, while jCMPL is a Java API; both can be used in applications to define sets and parameters, control the solving process, and read feasible solutions. CMPLServer is an XML-RPC-based web service for distributed and grid optimization, suitable for submitting large models to high-performance systems for remote solving. It supports local installation and server deployment, offering a degree of self-hosting capability.
The source text does not list commercial pricing or paid editions. In terms of licensing, CMPL and Coliop use GPLv3, while pyCMPL, jCMPL, and CMPLServer use LGPLv3. If deeply integrating them into a commercial project, you should assess the obligations imposed by GPL/LGPL licenses. In addition, licensing costs for commercial solvers such as Gurobi and CPLEX are not included in the provided information.
Its strengths are that it is open source, cross-platform, has broad solver integration, and provides an IDE, Python/Java APIs, and remote service components. Its limitations are that the text does not clarify documentation quality, community activity, or support channels, and its positioning mainly centers on linear optimization, with limited information about nonlinear or broader optimization scenarios. It is best suited for operations research optimization researchers, teaching users, engineering optimization developers, and teams that need to embed mathematical programming into Python/Java applications.
Based on the crawled text, it is not possible to determine the connectivity, download speed, or payment methods for coliop.org in mainland China, so its access status from China is marked as unknown. Alternatives worth considering include Pyomo, PuLP, JuMP, AMPL, GAMS, and OR-Tools.
⚠ This review is compiled from public sources and does not constitute a purchase recommendation. Verify all facts on the vendor's official site. Verify on coliop.org official site.
coliop.org is an Unknown Dev Tools provider. TG4G tracks its product information, an overall rating of 5.0/10, and a China-accessibility score of China direct-connect friendly. Click "Visit Official Site" to reach coliop.org directly.