Algorithm Of Stochastic Multi-objective Optimization Problem Based On Stochastic Optimization Method

This paper is devoted to efficient algorithms for global optimization of quadratic bilevel programming problem.As a breakthrough, starting with the linear bilevel programming problem, because it is the most simple form of all the bilevel programming problem,and the algorithm is extended to quadratic bilevel programming problems. In quadratic bilevel programming research,firstly, study on the convex quadratic bilevel programming problem,and then research on the more general case, and give the corresponding algorithms.In chapter three, the paper discusses the stochastic multi-objective integer linear optimization problem.Assume that random variable only exist on the right side of the constraint conditions, and the random variables follow the normal distribution. Convert this model into a deterministic multi-objective integer optimization model, the branch and bound method is used to get the optimal solution.In chapter four, the thesis shows that the random variable follows uniform distribution or normal distribution deterministic equivalent form in the chance constrained optimization model, and use the interactive algorithm to find the optimal solution.In chapter five, the thesis sets the model of water supply-allocation problem based on the relevant opportunity optimization model, and presents the optimal solution by using stochastic simulation of the genetic algorithm.