Harnessing the power of evolution

What is genetic programming and how is it useful?

Genetic programming or evolutionary algorithm is a method that can find optimized design solutions such as computer code, mathematical formula, microprocessor design or logistical plan.

Is genetic programming suitable for your use case?
Is the problem too complex to calculate analytically or by using brute force solution?
Are training data useless or unavailable altogether?
Is it simple to evaluate the quality of the solution, e.g. by measuring performance or against a checklist?

If you answered "yes" to these questions you should try out genetic programming and see if it works. Reach out to us for a preliminary evaluation!

Use cases

Completed use case: Workflow and process management

Prepared use case: Algorithmic circuit design

Our solution uses the input of business rules and outputs a completed workflow management code leading to significant savings in both analysis and programming/editing of the code.
It is specifically useful to quickly implement change requests and it provides analysts with real-time validation of their inputs and findings.

Genetic programming has already been successfully used to design specialized algorithmic circuits that are optimized for any of the required criteria like speed, energy consumption, error etc. We propose to take this a step further and optimize the circuits for a calculation as well. This should further improve the already significant benefits that genetic programming offers in algorithmic circuit design.

Completed use case: Logistical planning

Genetic programming has been shown in theory to be superior in logistical planning to state-of-the-art solutions. Practically it's most effective for more complex networks, e.g. those with high unpredictability, medium to large number of vehicles, with multiple cargo categories etc.
Our pilot has been able to automate the daily logistical plan generation and achieved over 7% savings in total travel distance for a medium delivery company.

Prepared use case: Circuit/algorithm coevolution

A step further beyond the circuit design, genetic programming offers the possibility to optimize in parallel both the circuit and the code the would run on it. This should improve performance even beyond that of custom-designed circuits.

About us

Center for Genetic Programming is a group of experts with background in technology, business and biology. Our objective is to develop and promote practical use of the genetic programming technology. Our team consists of analysts, programmers and external experts. We work by scouting relevant use cases, conducting necessary research and then developing business solutions to these use cases.

Photograph of Milos Cervenka

Milos Cervenka

Milos specializes in custom software development, mostly on projects involving AI, Big Data and Cloud solutions, and has led successful project teams both in business and startup environments. He studied biochemistry at Charles University in Prague and has three years experience in primary research.


Photograph of Ladislav Cervenka

Ladislav Cervenka

Ladislav’s expertise is in business strategy and financing. Over the past 10+ years he has been leading key business initiatives in North America, South America and in Europe, including a role with Novartis where he was responsible for 100+ project managers and 300+ IT projects. He completed his bachelor’s in finance / international business at Georgetown University, and his master’s in public health at Harvard University.



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