Research on Algorithm and Model for Indefinite Multi-objective Decision Making

Decision Support System is playing an important role in computer science, technology and engineering. Intelligent decision-making is one of the current hotspots in the decision support system research. Intelligent decisionmaking methods and algorithms are one of the most important basics and key cores in intelligent information processing, intelligent pervasive computing and so on. In this paper, conduct the research to two kinds of indefinite multi-objective decision making question: the indefinite sector and the indefinite language. (1) In view of multiattribute decision-making under linguistic setting, propose one new decision method. Firstly construct a range pole plan and introduce the policy-maker risk-preference weight. Then with three tuples (Limit low similarity, Risk degree, Risk-preference value) reflect the risk-degree existing in the decision-making process. At last, construct the riskweighted similarity measure operator (RWSMO) to measure the risk balance similarity's size between each of decision schemes and the range pole plan. (2) In view of multi-attribute decision-making under the indefinite sector, propose one new decision method based on the multiplevalued intuitive fuzzy sets.