The component-based business architecture integration of military information systems is a popu-lar 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 identifi cation tend to focus on software-level business components, and ignore such enterprise concs in business architectures as organizations and resources. Moreover, approaches to enterprise-level business component identi-fi cation have proven laborious. In this study, we propose a novel approach to enterprise-level business component identifi cation by considering overall cohesion, coupling, granularity, maintainability, and reusability. We fi rst defi ne 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 com-ponent identifi cation 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 e?cient for enterprise-level business component identifi cation than prevalent approaches.