I. Introduction
THERE is an abundance of business process modeling techniques that capture and address different aspects of a business process. A number of these process models allow further quantitative analysis and only a small structured process improvement. Compared with the large number of proposed business process modeling techniques and qualitative analysis approaches found in literature, business process optimization has received little coverage. A holistic approach towards business processes should capture a business process, provide the necessary means for bottleneck identification and performance analysis and-finally-generate alternative improved business processes based on specified objectives. But often this last part (business process optimization) is overlooked-if not completely neglected-in business process literature. This paper focuses on the various attributes that characterize a business process (e.g. cost, duration) and formulates a multi-objective optimization problem based on them. It then applies three popular evolutionary multi-objective optimization algorithms (EMOAs) and discusses the results.