Dynamic Programming and Genetic Algorithm for Business Processes Optimisation

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Mateusz Wibig 1,*

1. Senior Business Consultant, Logica Poland Operations, Warszawa, Poland

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2013.01.04

Received: 11 Mar. 2012 / Revised: 5 Jul. 2012 / Accepted: 4 Sep. 2012 / Published: 8 Dec. 2012

Index Terms

Petri Nets, Business Process Improvement, Simulation Based Optimization, Genetic Algorithm


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.

Cite This Paper

Mateusz Wibig, "Dynamic Programming and Genetic Algorithm for Business Processes Optimisation", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.1, pp.44-51, 2013.DOI:10.5815/ijisa.2013.01.04


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