The Model Of Fuzzy Optimal Selection Among Multi-Objectives And Its Application For The Allocation Of The Resources

Decision-making problems are widely used in the fields of society, economy, management and etc, and they usually follow the principle of mutual contradictions. The traditional theory of multi-objective decision-making is often confined in the phenomenon of certainty, while the one is often uncertain in real world. In general, phenomenon of uncertainty can be divided into two types: random and fuzzy. The probability theory is used to study and deal with random phenomenon, and the development of the fuzzy sets theory is used to deal with fuzzy phenomenon. The study of the paper can be summarized as follows: multi-objective decision-making model, the models of fuzzy optimal selection among multi-objectives in unit system and multi-systems, and multi-dimensional, multi-objective and multi-stage fuzzy optimization model.Firstly, this paper presents a multi-objective decision-making model and the definition of various solutions, discusses some of their properties, and gives the method of evaluating the function's ideal point. All this is the foundation of the following paper.Then, we give the single system's fuzzy optimization model by introducing the ideal point and the distance of sum of square weight. Weight and qualitative objectives are two types of primary preference information in fuzzy multi-objective decision-making. In determining the relative membership degree of qualitative objective, the paper firstly introduces the traditional pair wise comparsion, then qualitative grading scale table is used to determine the qualitative objective by the set-value statistics theory. Subjective weight to a certain extent depends on the expertise, and it is very subjective. The results are not necessarily consistent with the objective weighted method in reality. The theme adopts the method of synthesizing the subjective and objective weighted method to determine the ultimate weight factor. Taking into account the influence of the optimal weight to the local decision-making process and even the whole, and by using the weight perturbation transfer equation, the weight sensitive analysis will be done in the third chapter. Furthermore, the paper gives the model of multi-objective fuzzy optimal selection in the complex system. Currently, solving the model of multi-dimension , multi-objective and multi-phases fuzzy optimal selection, the DPSA arithmetic is used to reduce the dimensionality to solve it. This paper comes up with the arithmetic of reducing the dimension by the Lagrange Factor. At last, a specific example will be given in the fourth chapter.Finally, a summary is made and some problems to be further studied are given at the end of the paper.