The Research On The Multiobjective Full Coefficient Fuzzy Programming Problems

The complexity and diversity of modern society decides the universality of multiobjective optimization problems. Almost practical issues involve the multiobjective optimization; In the production and life, fuzzy phenomenon can be seen everywhere. It brings lots of difficulties to decision makers in the course of decision-making. The research on optimization problems has a very important theoretical and practical significance in multiobjective fuzzy environment.In this paper, we succeed to apply interactive satisficing methods to the multiobjective fuzzy programming. Firstly, in the multiobjective programming with fuzzy coefficients of objective functions, we give the value of the reference function and construct the auxiliary function, and then obain the single objective classic programming. At the same time, we use examples and test the effectiveness of the auxiliary function. In the multiobjective programming with fuzzy coefficient of constraint functions, given the reference membership function and the parameter in the range of deviation. Consequently, we reuse the membership function and continuity of the parameter in the constraint function, and then turn it into a classic extreme problem.Secondly, we analyze the large-scale multiobjective fuzzy linear programming problems with the block angular structure from three facts and use the Dandzigworlf decomposition method. At the same time, through decision makers updating the reference value, we use the interactive-genetic algorithm improved, which is applied to the convex multiobjective fuzzy nonlinear programming or the concave multiobjective fuzzy nonlinear programming.Lastly, in terms of the multi-level fuzzy programming characteristics, we provide two new objective function values which make decision makers fully satisfied and reluctantly accepted, and determine the fitness function, and then obain the solution satisfied by updating the smallest degree of satisfaction.