A common scientific method for decision making process is decision support system. Decision support system is a computer-based system which collects information from different sources and then organizes, analyzes and evaluates hypothesis with the help of available models. Because of lack of a comprehensive framework, users usually have problems which causes loss of the performance and effectiveness of decision support system. While main goal of using decision support system is supporting decisions, in available structures, there are no indications to any specific tools. In addition, previous studies show that evaluating the suggested alternatives is an effective factor to achieve a right decision. Nowadays data mining is an important method to extract information from large data sets. Also, multiple criteria decision making has recently been a crucial proceeding in decision making process. In this thesis, to overcome the mentioned problems and improve decision support system performance, a comprehensive and scientific framework has been presented through evaluation decisions module and integrating decision support system with data mining and multiple criteria decision making. Also, in order to justify effectiveness and performance of proposed structure, it is exploited in different fields and in each application, some innovations such as optimizing association rules through ANP, new algorithm for prioritizing to decision trees rules, and an approach to prioritize to available ltr"
