Engineering Optimization: Methods and Applications – serie

This book discusses generalized applications of energy storage systems using experimental, numerical, analytical, and optimization approaches. The book includes novel and hybrid optimization techniques developed for energy storage systems. It provides a range of applications of energy storage systems on a single platform.

This book discusses generalized applications of energy storage systems using experimental, numerical, analytical, and optimization approaches. The book includes novel and hybrid optimization techniques developed for energy storage systems. It provides a range of applications of energy storage systems on a single platform.

This book covers the latest advances in Cultural Algorithms, their general framework, different variants, hybridized versions with other meta-heuristic and search techniques, and their applications.

This book covers the latest advances in Cultural Algorithms, their general framework, different variants, hybridized versions with other meta-heuristic and search techniques, and their applications.

The book explores the latest developments in Operations Research and Artificial Intelligence and their transformative impact on healthcare systems and supply chains. It takes an in-depth look at emerging trends and their practical applications in critical areas such as healthcare delivery and supply chain management. Readers will discover how the integration of Operations Research and Artificial Intelligence can revolutionize decision-making, optimize resource allocation in healthcare, streamline patient flow, and enhance overall operational efficiency. The book also examines how these techniques are reshaping inventory management, procurement strategies, and the timely delivery of healthcare resources within supply chains. Packed with real-world case studies and practical examples, this book provides actionable insights into successfully implementing Operations Research and Artificial Intelligence techniques. It is designed for a broad audience, including researchers, healthcare professionals, supply chain experts, and students eager to stay ahead of the latest trends in these fields.This book equips readers with the knowledge and tools to overcome challenges and seize new opportunities. It aims to keep readers informed about cutting-edge innovations and help them understand the transformative potential of Operations Research and Artificial Intelligence in healthcare and supply chain management.

The book's objective is to develop mathematical structures that can be applied to real-life problems with sustainable goals. These optimization problems may include sustainable transport, cities, economic development, living, and tourism.

It addresses well-known models such as particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, population-based incremental learning, and grey wolf optimizer for training neural networks.

The book includes nature-inspired optimization techniques and their applications. It offers recent trends in the field of nature-inspired algorithms for solving real-life problems in various fields related to manufacturing, artificial intelligence, finance, etc.

This book provides a comprehensive review of the latest developments in optimization based learning algorithms within the field of electrical engineering. It discusses several optimization algorithms such as random forest algorithm, metaheuristic algorithm, scaled conjugate gradient descent algorithm, artificial bee colony algorithm etc.

This book presents state-of-the-art technologies in wind farm layout optimization and control to improve the current industry/research practice. The contents take readers towards a different kind of uncertainty handling through the discussion on several techniques enabling maximum energy harnessing out of uncertain situations. The book aims to give a detailed overview of such concepts in the first part, where the recent advancements in the fields of (i) Wind farm layout optimization, (ii) Multi-objective Optimization and Uncertainty handling in optimization methods, (iii) Development of Machine Learning-based surrogate models in optimization, and (iv) Different types of wake models for wind farms will be discussed. The second part will cover the application of the aforementioned techniques on the wind farm layout optimization and control through several chapters such as (i) Wind farm performance assessment using Computational Fluid Dynamics (CFD) tools, (ii) Artificial Neural Network (ANN) based hybrid wake models, (iii) Long Short-term Memory (LSTM) & Support Vector Regression (SVR) based forecasting and micro-siting, (iv) windfarm micro-siting using data-driven Robust Optimization (RO) as well as Generative Adversarial Networks (GANs), (v) Reinforcement learning (RL) based wind farm control and (vi) Application of eXplainable AI (XAI) tools for interpreting wind time-series data. In this manner, the book provides state-of-the-art techniques in the fields of multi-objective optimization, Evolutionary Algorithms, Machine Learning surrogate models, Bayesian Optimization, Data Analysis, and Optimization under Uncertainty and their applications in the field of wind energy generation that can be extremely generic and can be applied to many other engineering fields. This volume will be of interest to those in academia and industry.

This book concisely presents the optimization process and optimal control process with examples and simulations to help self-learning and better comprehension.

This edited book provides a platform to discuss the state-of-the-art developments associated with traditional and advanced single-/multi-objective criteria optimization methods for addressing problems of performance enhancement of the products and systems design.

This edited book provides a platform to discuss the state-of-the-art developments associated with traditional and advanced single-/multi-objective criteria optimization methods for addressing problems of performance enhancement of the products and systems design.

This contributed book focuses on optimization methods inspired by nature such as Harmony Search Algorithm, Drosophila Food-Search Algorithm, Cohort intelligence algorithm and its variations, fuzzy logic along with their hybridization variants.

This contributed book focuses on optimization methods inspired by nature such as Harmony Search Algorithm, Drosophila Food-Search Algorithm, Cohort intelligence algorithm and its variations, fuzzy logic along with their hybridization variants.

This book aims to provide a collection of state-of-the-art scientific and technical research papers related to machine learning-based algorithms in the field of optimization and engineering design.