In the rapidly changing manufacturing environment and marketplaces of today, the selection and evaluation of an appropriate manufacturing policy is a vital issue. However, this is a difficult task for decision makers, because manufacturing objectives are multiple, complex, conflict, and often vague. This paper presents a methodology for a satisfaction assessment of multi-objective schedules with results from the scheduling simulator. Various performance indicators(criteria) are aggregated into a satisfaction score for schedule assessment. We propose an aggregation methodology to provide a consistent and dimensionless degree of satisfaction using fuzzy logic and neural network technology to assess a production schedule respect to the company's global, objective and purpose. This paper extends TOPSIS, which is a common technique for MADM(Multi-Attribute Decision Making) problems, by using fuzzy logic to deal with inaccurate and linguistic information, such as expertise, and uses Extended TOPSIS as the aggregation tool.