Does anyone know of such a library that performs mathematical optimization (linear programming, convex optimization, or more general types of problems)? I'm looking for something like MATLAB, but with the ability to handle larger problems. Do I have to write my own implementations, or buy one of those commercial products (CPLEX and the like)?
Linear programming (LP), also called linear optimization, is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.
Mathematical optimization is used in much modern controller design. High-level controllers such as model predictive control (MPC) or real-time optimization (RTO) employ mathematical optimization.
Overview. Optimization solvers. Optimization solvers help improve decision-making around planning, allocating and scheduling scarce resources. They embed powerful algorithms that can solve mathematical programming models, constraint programming and constraint-based scheduling models.
A good answer is dependent on what you mean by "convex" and "more general" If you are trying to solve large or challenging linear or convex-quadratic optimization problems (especially with a discrete component to them), then it's hard to beat the main commercial solvers, gurobi, cplex and Dash unless money is a big issue for you. They all have clean JNI interfaces and are available on most major platforms.
The coin-or project has several optimizers and have a project for JNI interface. It is totally free (EPL license), but will take more work to set-up and probably not give you the same performance.
There is a linear optimization tool called lpsolve. It's written in C (I think) but comes with a Java/JNI wrapper (API is not very OO but it does the job). It's pretty easy to use and I have had it running quite happily and stably in a live system for the last year.
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