| 摘要 | 第7-8页 |
| Abstract | 第8-9页 |
| Acknowledgement | 第10-15页 |
| Nomenclature | 第15-20页 |
| Chapter 1 Introduction | 第20-30页 |
| 1.1 Motivation and Objective | 第21-24页 |
| 1.2 Research Thrusts | 第24-27页 |
| 1.2.1 Research Thrust 1: Robust Optimization Based on Sequential QuadraticProgramming | 第25页 |
| 1.2.2 Research Thrust 2: Advanced single-loop RO Algorithm | 第25-26页 |
| 1.2.3 Research Thrust 3: Sequential MOO and MDO Methods | 第26页 |
| 1.2.4 Research Thrust 4: Tolerance Design Optimization for Internal CombustionEngines | 第26-27页 |
| 1.3 Assumptions | 第27页 |
| 1.4 Organization of Dissertation | 第27-30页 |
| Chapter 2 Definitions and Terminologies | 第30-44页 |
| 2.1 Introduction | 第30页 |
| 2.2 Problem Definitions | 第30-35页 |
| 2.2.1 Robust Optimization (RO) | 第31-34页 |
| 2.2.2 Multi-disciplinary Design Optimization (MDO) | 第34-35页 |
| 2.2.3 Multi-objective Optimization (MOO) | 第35页 |
| 2.3 Sequential Quadratic Programming | 第35-37页 |
| 2.4 Matrix decomposition method for QPs subject to box constraints | 第37-38页 |
| 2.5 Design of Experiment (Do E) | 第38-39页 |
| 2.6 Gaussian Process (GP) Modeling | 第39-44页 |
| Chapter 3 Robust Optimization Based on Sequential Quadratic Programming | 第44-76页 |
| 3.1 Introduction | 第44-48页 |
| 3.2 Sequential Quadratic Programming Approach for Robust Optimization | 第48-61页 |
| 3.2.1 Approach to solve the objective robustness index | 第49-54页 |
| 3.2.2 Approach to solve the constraint robustness index | 第54-55页 |
| 3.2.3 SQP for Robust Optimization (SQP-RO) | 第55-59页 |
| 3.2.4 Computational efficiency of SQP-RO | 第59-61页 |
| 3.3 Test Examples and Comparison Results | 第61-74页 |
| 3.3.1 Nonlinear numerical example 1 | 第62-64页 |
| 3.3.2 Additional numerical examples | 第64-67页 |
| 3.3.3 Two-bar truss | 第67-69页 |
| 3.3.4 Speed Reducer | 第69-71页 |
| 3.3.5 Compression Spring | 第71-74页 |
| 3.4 Conclusion | 第74-76页 |
| Chapter 4 Advanced Robust Optimization Algorithm with a Single-looped Structure | 第76-106页 |
| 4.1 Introduction | 第76-79页 |
| 4.2 Utopian Solution to QPs Subject to Box Constraints | 第79-86页 |
| 4.2.1 Convex maximization (or concave minimization) problem | 第81-83页 |
| 4.2.2 Concave maximization (or convex minimization) problem | 第83-84页 |
| 4.2.3 Indefinite problem | 第84-86页 |
| 4.3 Advanced Sequential Quadratic Programming Approach for Robust Optimization(A-SQP-RO) | 第86-96页 |
| 4.3.1 Approach to Solve the Objective Robustness Index | 第86-89页 |
| 4.3.2 Approach to Solve the Constraint Robustness Index | 第89-92页 |
| 4.3.3 Advanced SQP for Robust Optimization (A-SQP-RO) | 第92-94页 |
| 4.3.4 Discussion of A-SQP-RO | 第94-96页 |
| 4.4 Test Examples and Comparison of Results | 第96-103页 |
| 4.4.1 Nonlinear Numerical Example 1 | 第96-100页 |
| 4.4.2 Additional Numerical Examples | 第100-101页 |
| 4.4.3 Two-bar Truss | 第101-102页 |
| 4.4.4 Speed Reducer | 第102-103页 |
| 4.5 Conclusion | 第103-106页 |
| Chapter 5 A New Sequential Multi-Disciplinary Optimization Method Based on A NovelSequential Multi-Objective Optimization Approach | 第106-140页 |
| 5.1 Introduction | 第106-110页 |
| 5.2 Background | 第110-111页 |
| 5.2.1 Definition for the monotonicity of a function along a certain direction | 第110-111页 |
| 5.2.2 Definition for the data sets | 第111页 |
| 5.3 S-MOO and S-MDO Methodologies | 第111-127页 |
| 5.3.1 Illustrative observations | 第112-118页 |
| 5.3.2 A novel Sequential MOO approach | 第118-119页 |
| 5.3.3 Handling of coupling variables and generation of data set Y | 第119-120页 |
| 5.3.4 A novel sequential MDO approach | 第120-123页 |
| 5.3.5 Steps of S-MOO and S-MDO | 第123-125页 |
| 5.3.6 Discussion of the proposed method | 第125-127页 |
| 5.4 Examples and Comparison of Results | 第127-139页 |
| 5.4.1 Test examples for S-MOO | 第127-134页 |
| 5.4.2 Test examples for S-MDO | 第134-139页 |
| 5.5 Conclusion | 第139-140页 |
| Chapter 6 Multi-disciplinary Tolerance Design Optimization for Gas Engines | 第140-168页 |
| 6.1 Introduction | 第140-146页 |
| 6.2 Robust tolerance optimization of compression ratio for a typical gas engine | 第146-149页 |
| 6.3 Gaussian process modeling for a typical gas engine | 第149-162页 |
| 6.3.1 Gaussian process modeling for performances vs. compression ratio | 第149-157页 |
| 6.3.2 Gaussian process modeling for friction loss vs. tolerance | 第157-162页 |
| 6.4 Multi-disciplinary tolerance design optimization problem | 第162-166页 |
| 6.5 Conclusion | 第166-168页 |
| Chapter 7 Conclusions and Future Work | 第168-176页 |
| 7.1 Concluding Remarks | 第168-172页 |
| 7.1.1 Robust Optimization Based on Sequential Quadratic Programming | 第169页 |
| 7.1.2 Advanced Robust Optimization Algorithm of a Single-looped Structure | 第169-170页 |
| 7.1.3 A sequential MDO approach based on a novel sequential MOO approach .. 1517.1.4 Application of proposed approaches for engineering examples | 第170-172页 |
| 7.2 Main contributions | 第172-173页 |
| 7.3 Future research directions | 第173-176页 |
| 7.3.1 Representing uncertainty with additional statistical information | 第173页 |
| 7.3.2 Problems with discrete variables and discontinuous or non-differentiablefunctions as well as black box problems | 第173-174页 |
| 7.3.3 Algorithms development for robust MDO problems | 第174-176页 |
| Bibliography | 第176-184页 |
| Publications | 第184页 |
