Products

Distributed Evolutionary Optimizer - C++ Library

Distributed Evolutionary Optimizer is our implementation of the differential evolution algorithm. The differential evolution (DE) is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. DE algorithms have three main advantages: finding the true global minimum regardless of the initial parameter values, fast convergence, and using a few control parameters. Our parallel implementation utilizes multi-processor and multi-core machines or it can be distributed over the network. We provide customization for our clients specific needs.

Please contact us for more information and pricing. 

mbp_products.png

Open Source

Distributed Evolutionary Optimizer - Python Module

At INFORISK we love and use open source products. Therefore, we have decided to make our Python implementation of the distributed differential evolution algorithm freely available. We are in the process of the final development and testing. Source code will be available for download on GitHub.

mbp_opensource.png