Abstract: The component-based business architecture integration of military information systems is a popular research topic in the field of military operational research. Identifying enterprise-level business components is an important issue in business architecture integration. Currently used methodologies for business component identification tend to focus on software-level business components, and ignore such enterprise concerns in business architectures as organizations and resources. Moreover, approaches to enterprise-level business component identification have proven laborious. In this study, we propose a novel approach to enterprise-level business component identification by considering overall cohesion, coupling, granularity, maintainability, and reusability. We first define and formulate enterprise-level business components based on the component business model and the Department of Defense Architecture Framework (DoDAF) models. To quantify the indices of business components, we formulate a create, read, update, and delete (CRUD) matrix and use six metrics as criteria. We then formulate business component identification as a multi-objective optimization problem and solve it by a novel meta-heuristic optimization algorithm called the ‘simulated annealing hybrid genetic algorithm (SHGA)‘. Case studies showed that our approach is more practical and efficient for enterprise-level business component identification than prevalent approaches.

Key words: Business architecture integration, Business component, Component identification, Create, read, update, and delete (CRUD) matrix, Heuristic

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