Global optimization solver

The ALGLIB numerical library offers a powerful global optimization solver, capable of efficiently handling unconstrained and constrained problems with box, linear and nonlinear constraints.

It is one of the fastest open-source global solvers (see the benchmark), available in C++, C#, Java and several other programming languages, under both free and commercial editions.

Global optimization solver overview

Key features

The key features of the ALGLIB global optimization solver include:

• Performance. The solver implements many algorithmic improvements and low level optimizations to improve its speed.
• Parallelism support. The commercial version of the solver can parallelize target function evaluations, achieving impressive speedup over the free edition.
• Robustness. The solver reliably handles degenerate problems.
• Convenience. A uniform API is provided for all combinations of solvers and languages.

Benchmark

In order to evaluate performance and robustness of our differential evolution solver we compared it with several metaheuristic solvers from other well-known open source software packages. We used a small-dimensional subset of the CUTEst set of test problems. See the benchmark page for more information about the benchmark setup.

The chart above clearly shows that ALGLIB is the fastest solver amongst ones compared.

Programming languages supported

ALGLIB supports many programming languages, including C++, C#, Java, Python, and others:

• C++ version. Highly optimized, portable (x86/x64/ARM, works on Windows, Linux, and POSIX systems), and is a self-contained library
• C# version. Unified C# API for two backends - a fully managed C# implementation and a high-performance native computational core written in C
• Java, Python and other languages. A wrapper for a high-performance native computational core written in C. Seamless integration with the target programming language

A distinctive feature of ALGLIB is that it provides exactly the same API in all programming languages. This is achieved with our exclusive technology of automatic code translation and wrapper generation.

Algorithms

Global optimization (GO) is closely related to derivative-free optimization because GO problems are often nonsmooth and noisy. The most popular GO algorithms (differential evolution, genetic algorithms, particle swarm optimization) are inherently derivative-free. That's why global and derivative-free optimization functionality in ALGLIB is provided by the same subpackage, mindf.

As of the most recent ALGLIB release, the global optimization solver uses constrained differential evolution as its underlying algorithm. Our implementation of the DE algorithm uses an award-winning adaptive parameter tuning strategy EPSDE (proposed by R.Mallipeddi and P.N.Suganthan), which is completely free from tunable parameters, automatically choosing crossover rate and mutation probability.

EPSDE successfully competes with other global methods like genetic algorithms (GA) and particle swarm optimization (PSO), producing comparable or better results with no tuning. It also efficiently handles nonsmooth and even discontinuous problems.

ALGLIB Reference Manual entry for the mindf subpackage includes API description and several examples.