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In this paper, we consider a decision problem arising from higher degree research student recruitment process in a university environment. The problem is to recruit a number of research students by maximizing the sum of a performance index satisfying a number of constraints, such as supervision capacity and resource limitation. The problem is dynamic in nature as the number of eligible applicants, the supervision capacity, completion time, funding for scholarships, and other resources vary from period to period and they are difficult to predict in advance. In this research, we have developed a mathematical model to represent this dynamic decision problem and adopted an evolutionary algorithm-based approach to solve the problem. We have demonstrated how the recruitment decision can be made with a defined objective and how the model can be used for long-run planning for improvement of higher degree research program.