This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology, orthogonal experimental design, and uniform experimental design, are all performed; the conditions of the material performance utility with desirable value and robust assessment are included; the discretization treatment of complicated integral in the evaluation is presented. The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone.This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.
This book illuminates the fundamental principle and applications of probability-based multi-objective optimization for material selection systematically, in which a brand new concept of preferable probability and its assessment as well as other treatments are introduced by authors for the first time. Hybrids of the new approach with experimental design methodologies, such as response surface methodology, orthogonal experimental design, and uniform experimental design, are all performed; the conditions of the material performance utility with desirable value and robust assessment are included; the discretization treatment of complicated integral in the evaluation is presented.
The authors wish this work will cast a brick to attract jade and would make its contributions to relevant fields as a paving stone.
This book can be used as a textbook for postgraduate and advanced undergraduate students in material relevant majors, and a reference book for scientists and engineers digging in the related fields.
Chapter 1 Introduction
It introduces the general idea of multiple objective optimization in material selection, the status of the applications of multiple objective optimization in material selection, the previous methods and their shortcomings, etc.
Chapter 2 Probability-Based Multi-Objective Optimization and Applications
It describes the general idea of probability-based multiple objective optimization, the basis of theoretic meaning in probability theory, the algorithm, and the features, etc. Applications of materials selection, and some other applications in more broader and general issues are given.
Chapter 3 Extension in Condition of the Utility with Interval Number
It describes the extension of probability-based multiple objective optimization in condition of the utility with interval number, some applications of materials selection are given.
Chapter 4 Extension in Condition of the Utility with Desirable Value
It describes the extension of probability-based multiple objective optimization in condition of the utility with desirable value, some applications of materials selection are given.
Chapter 5 Combination of Probability-Based Multi-Objective Optimization with Test Design Methods
It describes the combination of probability-based multi-objective optimization with test design methods, such as orthogonal test design and uniform experimental design. Some applications of materials selection are given.
Chapter 6 Application of Regression Analysis in the Probability-Based Multi-Objective Optimization
Regression analysis is applied to the probability-based multi-objective optimization, it provides a more accurate prediction, especially for test design methods. Some applications of materials selection are given.
Chapter 7 Concluding Remarks
Conclusion of this book and reviewing the up-to-date progress.
