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This paper discusses the problem of business process design and attribute optimization within a multi-objective evolutionary framework. Business process design and attribute optimization is considered as the problem of constructing feasible business process designs with optimum attribute values such as duration and cost. The feasibility of a process design is based on: (i) the process requirements such as the required input and the expected output resources and (ii) the connectivity of the participating tasks in the process design through their input and output resources. The proposed approach involves the application of the evolutionary multi objective optimization algorithm (EMOOA) non-dominated sorting genetic algorithm II (NSGA2) in an attempt to generate a series of diverse optimized business process designs for the same process requirements. The proposed optimization framework introduces a quantitative representation of business processes involving two matrices one for capturing the process design and one for calculating and evaluating the process attributes. It also introduces an algorithm that checks the feasibility of each candidate solution (Le. process design). The results demonstrate that for a variety of experimental problems NSGA2 produces a satisfactory number of optimized design alternatives considering the problem complexity and high rate of infeasibility.