A New Approach Based on Genetic Algorithm for Prioritizing Quality Scenarios in Enterprise Architecture Evaluation

Enterprise Architecture is an approach for understanding, engineering, and managing all enterprise elements and their relationships. In order to better explain the concepts defined in the quality attributes in enterprise architecture and their relationships, the quality scenarios are used. Because of the breadth and variety of enterprise architecture quality scenarios, the cost of implementation scenarios is high. Therefore, prioritization and selection of optimal scenarios, in terms of quality attributes satisfaction, before implementation, is very important. Due to the diversity of stakeholders, large number of scenarios and possible selections, prioritization scenarios involves searching a large state space and considering all of the possible selections which is not precise. Genetic Algorithm is the intelligent algorithm that solves the problems based on metaheuristic search. This paper presents an innovative method for prioritizing quality scenarios, based on the knowledge and experience of stakeholders using genetic algorithm. The validity of proposed algorithm is evaluated in two case studies and it’s precision is compared with similar methods. The results of evaluation show the correctness and performance of this algorithm to prioritize large number of quality scenarios with higher precision and lower computational complexity in comparing to other methods. Keyword: Genetic Algorithm, Quality Scenario, Enterprise Architecture Evaluation

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