Overview The Present Research Education Optimization Theory Applications

This book focuses on recent research in modern optimization and its implications in control and data analysis. This book is a collection of papers from the conference “Optimization and Its Applications in Control and Data Science” dedicated to Professor Boris T. Polyak, which was held in Moscow, Russia on May 13-15, 2015. This book reflects developments in theory and applications rooted by Professor Polyak’s fundamental contributions to constrained and unconstrained optimization, differentiable and nonsmooth functions, control theory and approximation. Each paper focuses on techniques for solving complex optimization problems in different application areas and recent developments in optimization theory and methods. Open problems in optimization, game theory and control theory are included in this collection which will interest engineers and researchers working with efficient algorithms and software for solving optimization problems in market and data analysis. Theoreticians in operations research, applied mathematics, algorithm design, artificial intelligence, machine learning, and software engineering will find this book useful and graduate students will find the state-of-the-art research valuable.

Extremal Optimization: Fundamentals, Algorithms, and Applications introduces state-of-the-art extremal optimization (EO) and modified EO (MEO) solutions from fundamentals, methodologies, and algorithms to applications based on numerous classic publications and the authors’ recent original research results. It promotes the movement of EO from academic study to practical applications. The book covers four aspects, beginning with a general review of real-world optimization problems and popular solutions with a focus on computational complexity, such as "NP-hard" and the "phase transitions" occurring on the search landscape. Next, it introduces computational extremal dynamics and its applications in EO from principles, mechanisms, and algorithms to the experiments on some benchmark problems such as TSP, spin glass, Max-SAT (maximum satisfiability), and graph partition. It then presents studies on the fundamental features of search dynamics and mechanisms in EO with a focus on self-organized optimization, evolutionary probability distribution, and structure features (e.g., backbones), which are based on the authors’ recent research results. Finally, it discusses applications of EO and MEO in multiobjective optimization, systems modeling, intelligent control, and production scheduling. The authors present the advanced features of EO in solving NP-hard problems through problem formulation, algorithms, and simulation studies on popular benchmarks and industrial applications. They also focus on the development of MEO and its applications. This book can be used as a reference for graduate students, research developers, and practical engineers who work on developing optimization solutions for those complex systems with hardness that cannot be solved with mathematical optimization or other computational intelligence, such as evolutionary computations.

This book constitutes refereed proceedings of the 21st International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2022, held in Petrozavodsk, Russia, in July 2022. The 21 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 88 submissions. The papers in the volume are organised according to the following topical headings: ​invited talks; integer programming and combinatorial optimization; mathematical programming; game theory and optimal control; operational research applications.

With Response Surface Methods - Theory, Applications, and Optimization Techniques, one can unlock the full potential of experimental designs. This comprehensive guide delves into the complexity of Response Surface Methodology (RSM), offering both foundational theories and cutting-edge applications. This book provides novices and experienced practitioners with the tools and knowledge required to optimize processes, enhance quality, and drive innovation. Through a mix of theoretical insights and practical case studies, one addresses how RSM can be applied across a diverse set of fields, including engineering, chemistry, biology, health care, and more. Inside, readers will find fundamental concepts for understanding the core principles of RSM, experimental designs, applications, optimization techniques, advanced topics, and an extensive bibliography. This book is an essential resource for researchers, engineers, and scientists aiming to leverage RSM for superior outcomes. With broad contributions from leading experts in the field, Response Surface Methods - Theory, Applications, and Optimization Techniques stands as a definitive guide for mastering the art and science of experimental optimization. Optimize your work, streamline your processes, and achieve outstanding results with this essential volume.

This book constitutes refereed proceedings of the 20th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2021, held in Irkutsk, Russia, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 31 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 102 submissions. The papers in the volume are organised according to the following topical headings: continuous optimization; integer programming and combinatorial optimization; operational research applications; optimal control.