Abstract—Mining Sequential Patterns in large databases has become

Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, the algorithms for performing sequential pattern mining can assure optimum solutions but they do not take into consideration the time taken to reach such solutions. In this paper we propose a new algorithm based on genetic concepts which gives, may be a non-optimal solution but in a reasonable time (polynomial) of execution.