Mateusz Wibig

Work place: Senior Business Consultant, Logica Poland Operations, Warszawa, Poland



Research Interests: Computer systems and computational processes, Decision Support System


WIBIG Mateusz (1982 - ) He received M.Sc. and Eng. degree from The Technical University of Lodz in 2006.

In 2006 he started working in Technology Department of Deloitte Business Consulting, providing management and technological consulting services for the biggest Central Europe companies and organizations. In 2012 he joined Logica Poland Operations, now part of CGI, as a leading consultant and main architect in Poland.

In the same time he conducted his studies on artificial intelligence applications. His research interests include decision support systems, business processes modelling and bio-inspired algorithms.  He is also a guest lecturer in data warehouses at the Technical University of Lodz.

Author Articles
Dynamic Programming and Genetic Algorithm for Business Processes Optimisation

By Mateusz Wibig

DOI:, Pub. Date: 8 Dec. 2012

There are many business process modelling techniques, which allow to capture features of those processes, but graphical, diagrammatic models seems to be used most in companies and organizations. Although the modelling notations are more and more mature and can be used not only to visualise the process idea but also to implement it in the workflow solution and although modern software allows us to gather a lot of data for analysis purposes, there is still not much commercial used business process optimisation methods. 
In this paper the scheduling / optimisation method for automatic task scheduling in business processes models is described. The Petri Net model is used, but it can be easily applied to any other modelling notation, where the process is presented as a set of tasks, i.e. BPMN (Business Process Modelling Notation). 
The method uses Petri Nets’, business processes’ scalability and dynamic programming concept to reduce the necessary computations, by revising only those parts of the model, to which the change was applied.

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