Research On Effect Probability-based Decision-making Method

It is an inevitable decision making problem to juggle multiple objectives in production practice, social occasions, policy making and many other activities. Although multi-objective programming theory has formed to this kind problem, the existing methods still can not solve the uncertainties of decision problems under the complex decision environment. So there is an important theoretical and realistic significance to study on multi-objective programming decision methods in complex decision environment.Random decision environment and fuzzy decision environment are two main complex uncertain decision environment. For establishing high effective decision methods:1) In random decision environment, we first study on the probability calculation problem of random events who has fuzziness and proposed the level effect function which reflects the fuzzy decision consciousness of decision makers. Naturally, we further establish the probability measurement of fuzzy events based on cut set effect, short for effect probability and abbreviated as EP. Then we give concrete probability formulas of several special fuzzy events combined with several special random environment(or probability distributions). Finally, we regard the fuzzy objectives in random multi-objective problems as fuzzy events, then propose the multi-objective programming based on effect probability,abbreviated as MP-EP. 2) In the fuzzy decision environment, the existing multi-objective programming can not embody the reliability degree. For this shortcoming, we describe the fuzzy decision objectives as fuzzy numbers and present the multi-objective programming based on satisfied degree, abbreviated as MP-SD. Theoretical analysis and practice show:effect probability is an effective method for complex system uncertainty processing; MP-EP and MP- SD both enrich the existing multi-objective decision theory and can be widely applied to the complex system optimization, portfolio analysis, etc.