Research On Method And Application Of Robust Optimization For Uncertainty System

From the view of philosophy, uncertainty is the inherent phenomenon of everything. In the subject of system science and system engineering, it is necessary to be taken into accounted hi the process of making decision to system and process, otherwise, the decision making is not be called scientific decision making 0 Uncertainty includes system structural uncertainty and systems parameter uncertainty, et al. The system optimization problems with parameter uncertainty and some applications are studied in the dissertation.The research object of the dissertation is system optimization for the uncertainty system with interval model parameter. Based Interval mathematics and regret, an alternative problem of the uncertainty problem with tri-objective optimization is proposed. For this ami, Integrated some intelligent methods , some efficient optimization methods are proposed in this dissertation such as hybrid genetic optimization method^ optimization based on dynamics and interactive multi-objective method based on unbundled objective functions, and so on . The hybrid optimization methods used to solve Minimax optimization in the dissertation is applied to Robust controller design. In the mean time, a interactive multi-objective optimization algorithm is proposed. Finally, based the successful practice in the field of water industrial system, some research prospects in the field are proposed.The marn contributions and research work are as follows:1. Based on the concept of order and regret, A new tri-multi-objective optimization model is developed which is alternative used to solve the uncertainty optimization system with interval model parameter ?In particular, the uncertainty optimization model exits in many fields, such as economic and Industrial fields. The Tri-multi-objective optimization model include three functions: the first function is used to express the mathematical expectation in the uncertainty environment, the second function is used to express the robust property through a uncertainty degree function, the final function is used to express the mind of the decision makerthrough a regret function 2. The Tri-Multi-objective optimization is very important in order to solve the uncertainty optimization problem. And the basis of the multi-objective optimization is single objective optimization and MINIMAX optimization?In the dissertation, some effective optimization methods are developed for the single objective optimization?The effective methods are as follows:2.1 Hybrid Simplex-Genetic optimization method 0 One of the main obstacles in applying genetic algorithms (GAs) to complex problems has been the high computational cost due to their slow convergence rate. To alleviate this difficulty, we developed a hybrid approach that combines GA with simplex method in function optimization. In the same way, the hybrid simplex-Genetic method is applied to solve the continuous minimax optimization. Some benchmark problems are tested in the real space and showed the results.2.2 Dynamical optimization method. The Lyapunov theorem and Lasalle invariance principle are applied to optimization sub-problem in augmented Lagrange multiplier method. A dynamical system is built which is satisfied to Lyapunov function whose energy function is penalty function in augmented Lagrange multiplier method. The dynamical system is global stable, and its stable solution is the optimization solution of sub-problem in augmented Lagrange multiplier method according to Lasalle invariance principle. Finally a complete optimization algorithm is developed.3. A new unbundled interactive multi-objective optimization method used to solve the Tri-multi-objective optimization is developed. In the new interactive multi-objective optimization, the functions are unbundled to three classes: the first is theset whose value should be improved ; the second is the set whose value are allowed to relax(impair)( ) and the final is the set whose value areaccepted)(such that {the set of all the objective...