OptSolvX

OptSolvX is a flexible Java library for solving linear programming (LP) problems with multiple interchangeable solver backends.
It provides a clean, test-driven API for building, comparing and extending LP solvers.
OptSolvX is intended for applications in mathematics, research, and systems biology.

► Features

• Solver-agnostic LP core: AbstractLPModel, Variable, Constraint, OptimizationDirection, LPSolution
• Unified solver adapter interface: LPSolverAdapter
• Pluggable backends: CommonsMathSolver (ready), OjAlgoSolver (planned)
• Test-driven development with JUnit 5
• Clean logging & validation (build checks, bounds, relations)
• Easy to extend with custom backends; demo included

► Status

• LP modeling & solving: maximize/minimize, EQ/LEQ/GEQ constraints, variable bounds, build() workflow
• Backends: Commons Math adapter ready; ojAlgo adapter planned
• Builds: Java 22 by default; optional Java 8 bytecode via compat8 profile (classifier jdk8)

► Installation

Requirements: Maven ≥ 3.9, Java 22 (default).

Optional: build an additional Java 8 bytecode artifact via profile compat8.

git clone https://github.com/draeger-lab/OptSolvX.git
cd OptSolvX

Default (Java 22) - installs to local Maven repo

mvn clean install

Optional: Java 8 bytecode JAR (classifier jdk8)

mvn -P compat8 -DskipTests clean package

Artifacts

• target/optsolvx-.jar - Java 22 (default)
• target/optsolvx--jdk8.jar - Java 8 bytecode (compatibility)

► Testing

All mathematical LP tests are found in src/test/java/org/optsolvx/tests/lp.

Biological and advanced tests (e.g., with SBML) will be added in the future under src/test/java/org/optsolvx/bio.

Run all tests with:

mvn test

► Quick Demo

Run the built-in demo (max x + y with two constraints) using the Commons Math backend.

From IDE: run org.optsolvx.solver.SolverDemo.

From Maven (CLI):

mvn -q exec:java
# If needed:
# mvn -q -DskipTests exec:java -Dexec.mainClass=org.optsolvx.solver.SolverDemo

Expected Output:

Variable values: {x=3.0, y=0.5}
Objective: 3.5
Feasible:  true

Optional debug: enable verbose model logging in the demo:

model.setDebug(true); // call before model.build()

► Contribution

Contributions and feedback are welcome! Please open issues or pull requests on GitHub.

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State of this README as of: 20.08.25