Probability-Based Multi-objective Optimization for Material Selection

This book explores innovative probability-based optimization techniques for material selection, integrating experimental design methodologies and practical applications.

The second edition of Probability-Based Multi-objective Optimization for Material Selection offers a comprehensive exploration of probability-based multi-objective optimization techniques, particularly in the context of material selection from a system theory perspective. This edition introduces innovative concepts such as preferable probability and its assessment, providing readers with a fresh outlook on optimization methodologies. The authors integrate these new ideas with established experimental design methodologies, including response surface methodology, orthogonal experimental design, and uniform experimental design, enhancing the practical applications of the theories discussed.

In addition to the theoretical underpinnings, the book delves into various practical applications, including robustness assessment and performance utility, ensuring that the methodologies presented are not only theoretical but also applicable in real-world scenarios. The integration of fuzzy-based approaches and cluster analysis further enriches the content, making it relevant for a wide range of applications, from portfolio investment to solving shortest path problems. The authors aim to equip readers with the tools necessary to navigate complex decision-making processes in material selection effectively.

Designed for postgraduate and advanced undergraduate students, Probability-Based Multi-objective Optimization for Material Selection also serves as an essential reference for scientists and engineers. The authors hope that this work will inspire further exploration and innovation in the field, acting as a stepping stone for future research and applications.