B. Fathi Ajirlou - MS. of Industrial Engineering, System Architecture Pioneers Co., Tehran, Iran.
A. Fathi Ajirlou - Ms. Student of Industrial Engineering, Khatam University, Tehran, Iran.
P. Sarmadi Khezerlou - MS. Student of Industrial Engineering, Industrial Engineering Department of Khaje Nasir University of Technology, Iran.

Information Systems Planning becomes the major concern for effective implementation of ICT Master Plans. ISP is the process of deciding the objectives for organizational and identifying potential information systems which the organization should implement. The many ISP methodologies are implemented to produce satisfactory IS strategy plans. Business Systems Planning and Information Engineering are two reputed methodologies for ISP. The main aim of these methodologies is to secure structured methods and models for nterpreting and transforming of enterprise business needs to information systems by analyzing of business information needs and structuring them into separable sub-systems. In BSP and IE methodologies, these sub-systems obtained after clustering process of the CRUD matrix. In literature, many models have tried to solve this problem by different approaches and algorithms. But they fail to employ the business strategies effectively. In this research, we propose a subject function-based clustering technique that introduces the goals and efficiency measures of identifying of business areas. The business areas identification problem is considered as a quadratic assignment problem, and as QAP is NP-hard, genetic algorithm is employed as solving algorithm.

Information Systems Planning, Business Areas, Information Engineering, CRUD matrix, Clustering