A Class Of Two-story Multi-objective Optimal Solution Of Mixed Model

Since the seventies of last century, levels of decentralized decision-making system optimization been studied. Life in the real system needs, most of the second floor can be seen as a decision-making system, all multi-layer decision-making system can be viewed as a series of complex decision-making system. Regulation of the second floor has a special mathematical programming structure, is a kind of constraint, and constraints in the optimization problem with another extremal problem is a static Stackelberg Strategies and Minimax Problems with, have their own background and practical value, has been strong interest, such as economics, applied mathematics, management science, operations research, systems science and so many areas, and attracted the interest of many scholars and experts.This paper studies a bilevel programming of several issues. First, investment decisions,we will issue the actual goal of the abstract into the two-hybrid optimization model, using multiplication and division targets minimization method, structure evaluation function, the two target models into a single linear fractional binding planning issues, can be based on the related properties of fractional programming, re-use fractional programming interior point algorithm, the new interior point iteration stop condition obtained by changing the mix of optimization models similar point.Second, great for Solving Bilevel Programming Problem, we use the reduced gradient method and the least amount of change are calculated as linear fractional programming all the vertices, different from the traditional method of simply the culmination of the optimal solution obtained. Finally, research on multiobjective nonlinear programming of the new algorithm, the new algorithm improved by linear weighted method of multiple targets on the minimization constructor, we calculate the expected value programming and then determine under the relevant theorems expect Solutions whether the objective is to minimize the more efficient solution or a weak efficient solution. Then we evaluated the use of fgoalattain function of its optimal solution, the advantage of the new algorithm can be efficiently solved with a single solution or weak efficient solution.