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In this paper is analyzed and modeled the problem of discovery process models, in order to apply metaheuristic algorithms based on a point and populations. There are two main reasons for the growing interest to improving the efficiency of the discovery algorithms in process mining. First or all, the information systems, that support business processes in organizations, record the details of the executions. These contain a potential knowledge for decision making. In addition to the growing need to support business processes in competitive and rapidly changing environments. In order to meet the objective of this work that is selected best suited metaheuristics algorithms to the problem: The Hill Climbing and Evolutionary Strategy. The main contribution consists in modeling a first approach to the problem of finding models using metaheuristic strategies. [ABSTRACT FROM AUTHOR]