Genetic Algorithm Based on Multiple Population in a Business Process Optimization Issue

In a competitive environment, enterprises success depends on the effectiveness of their business processes, which leads to the search of a continuous improvement in the time. This kind of improvement is called business process optimization. Yet, two major challenges often prevent processes optimization. First, the skills of the analysts to choose the right process among a number of propositions. Second, the techniques applied to generate and evaluate solutions during optimization process are poor and do not include all relevant data. Our Evolutionary Business Process Optimization approach addresses these challenges through a well-defined mathematical representation and a novel evolutionary algorithm as optimization facilities. In this paper, we focus to use of a formalized process optimization approach for generating and improving business process designs.