Joshua Knowles – författare

Soft Computing is a complex of methodologies that embraces approximate reasoning, imprecision, uncertainty and partial truth in order to mimic the remarkable human capability of making decisions in real-life, ambiguous environments. Soft Computing has therefore become popular in developing systems that encapsulate human expertise. Applications of Soft Computing: Recent Trends contains a collection of papers that were presented at the 10th Online World Conference on Soft Computing in Industrial Applications, held in September 2005. This carefully edited book provides a comprehensive overview of the recent advances in the industrial applications of soft computing and covers a wide range of application areas, including optimisation, data analysis and data mining, computer graphics and vision, prediction and diagnosis, design, intelligent control, and traffic and transportation systems. The book is aimed at researchers and professional engineers who are engaged in developing and applying intelligent systems. It is also suitable as wider reading for science and engineering postgraduate students.

Multiobjective problems involve several competing measures of solution quality, and multiobjective evolutionary algorithms (MOEAs) and multiobjective problem solving have become important topics of research in the evolutionary computation community over the past 10 years. This is an advanced text aimed at researchers and practitioners in the area of search and optimization.

The book focuses on how MOEAs and related techniques can be used to solve problems, particularly in the disciplines of science and engineering. Contributions by leading researchers show how the concepts of multiobjective optimization can be used to reformulate and resolve problems in broad areas such as constrained optimization, coevolution, classification, inverse modelling and design. The book is distinguished from other texts on MOEAs in that it is not primarily about the algorithms, nor specific applications, but about the concepts and processes involved in solving problems using a multiobjective approach. Each chapter contributes to the central, deep concepts and themes of the book: evaluating the utility of the multiobjective approach; discussing alternative problem formulations; showing how problem formulation affects the search process; and examining solution selection and decision making.

The book will be of benefit to researchers, practitioners and graduate students engaged with optimization-based problem solving. For multiobjective optimization experts, the book is an up-to-date account of emerging and advanced topics; for others, the book indicates how the multiobjective approach can lead to fresh insights.

This two-volume set LNCS 15512-15513 constitutes the proceedings of the 13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025, held in Canberra, ACT, Australia, in March 2025.

The 38 full papers and 2 extended abstracts presented in this book were carefully reviewed and selected from 63 submissions. The papers are divided into the following topical sections:

Part I : Algorithm design; Benchmarking; Applications.

Part II : Algorithm analysis; Surrogates and machine learning; Multi-criteria decision support.