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The model-based approach for carrying out classification and identification of tasks has led to the pervading progress o......more
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This book presents cutting-edge algorithms for solving large-scale quadratic programming (QP) and/or QCQP. While applyin......more
An introduction to gradient-based stochastic optimization that integrates theory and implementation This book explains g......more
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Riemannian optimization is a powerful tool for decision-making in situations where the data and decision space are struc......more
The book provides a comprehensive review of multiple information sources and multi-fidelity Bayesian optimization, speci......more
The famous simplex method, invented by George B. Dantzig in 1947, moves from vertex to vertex in the underlying polyhedr......more
Mathematics of Networks: Modulus Theory and Convex Optimization explores the question: "What can be learned by adapting ......more
Causal Machine Learning (CausalML) is an umbrella term for machine learning methods that formalize the data generation p......more
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This book is a research monograph with specialized mathematical preliminaries. It presents an original range space and c......more
This book is intended for a technical audience with advanced learning and in-depth analysis of the latest real-world dev......more
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The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming.......more
The text is divided into three main parts: unconstrained optimization, constrained optimization, and linear programming.......more
This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (......more
Optimization processes are present in nearly all human activities, aiming to reduce time and expenses, conserve resource......more
Optimization Methods for Finite Element Analysis and Design describes recent developments in Finite Element Methods (FEM......more
This comprehensive volume explores differentiation and integration, detailing their theories, concepts, and formulations......more
This book LNCS 15681 constitutes the refereed proceedings of the 24th International Conference on Mathematical Optimizat......more
This book is an introduction to reconstruction concepts and its applications for solving some network optimization probl......more
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Decision Making Optimization Models for Business Partnerships extends non-parametric Data Envelopment Analysis (DEA) and......more
This contributed volume is dedicated to Academician Gradimir V. Milovanovic on his 75th birthday and contains recent res......more
This book is an excellent collection of various topics of mathematics which include numerical methods, integral equation......more
This open access book is a coherent and accessible source of knowledge on flexibility services for energy. Local flexibi......more
Meta-heuristics have been deployed to solve many hard combinatorial and optimization problems. Parameterization of meta-......more
A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stoch......more
This thesis addresses the problem of optimally selecting and specifying satellite payloads for inclusion on a satellite ......more
A new class of algorithms is introduced and analyzed for bound and linearly constrained optimization problems with stoch......more
Meta-heuristics have been deployed to solve many hard combinatorial and optimization problems. Parameterization of meta-......more
The field of project scheduling has received a great deal of study for many years with a steady evolution of problem com......more
The surveillance mission requires aircraft to fly from a starting point through defended terrain to targets and return t......more
Deriving weights for a Value Focused Thinking (VFT) hierarchy demands considerable time and input from Decision Makers (......more
Deriving weights for a Value Focused Thinking (VFT) hierarchy demands considerable time and input from Decision Makers (......more
The field of project scheduling has received a great deal of study for many years with a steady evolution of problem com......more
This thesis addresses the problem of optimally selecting and specifying satellite payloads for inclusion on a satellite ......more
The surveillance mission requires aircraft to fly from a starting point through defended terrain to targets and return t......more
This book offers an up-to-date description of relaxation/approximation and decomposition techniques, demonstrating how t......more
Mathematical optimization and machine learning are closely related. This proceedings volume of the Thematic Einstein Sem......more
This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their applica......more
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The book presents powerful optimization approaches for integrating AI into daily life. This book explores how heuristic ......more
Optimization is an area in constant evolution. The search for robust optimization techniques to deal with the highly non......more
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Markov Decision Processes (MDPs) form a cornerstone of applied probability, with over 50 years of rich research history.......more
This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in s......more
This book provides insights into contemporary issues and challenges concerning operational research and related mathemat......more
The book presents a detailed and unified treatment of the theory and applications of optimization applied to control and......more
This book delves into the intricate world of fixed point theory, focusing on the Krasnoselskii-Mann method to tackle com......more
This book provides an introduction to the mathematical theory of games using both classical methods and optimization the......more
This book provides an introduction to the mathematical theory of games using both classical methods and optimization the......more
Moth-Flame Optimization algorithm is an emerging meta-heuristic published in 2015. This book provides in-depth analysis ......more
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The comprehensive volume focuses on both research and survey papers presenting results in a broad spectrum of subjects i......more
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In the rapidly evolving domain of computational problem-solving, this book delves into the cutting-edge Automatic Genera......more
Apply satisfiability to a range of difficult problems The Boolean Satisfiability Problem (SAT) is one of the most famous......more
This textbook is carefully designed as an early undergraduate introduction to the calculus of several real variables. Th......more
Get a detailed introduction to quantum computing and quantum machine learning, with a focus on finance-related applicati......more
The model-based approach for carrying out the classification and identification of tasks has led to progression of the m......more
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Comprehensive overview of the fledgling domain of federated learning (FL), explaining emerging FL methods, architectural......more
This textbook is an introduction to global optimization, which treats mathematical facts stringently on the one hand, bu......more
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Decision Superhero is a modern practical guide to making better decisions using probability. Understand essential psycho......more
Decision Superhero is a modern practical guide to making better decisions using probability. Understand essential psycho......more
This thesis deals with an optimization problem from the field of theoretical plasma physics. Specifically, it deals with......more
The use of spreadsheets to obtain solutions to a diverse array of examples offers a reader-friendly way of addressing a ......more
Hybrid Genetic Optimization for IC Chip Thermal Control: with MATLAB(R) applications focuses on the detailed optimizatio......more
This book provides different approaches used to analyze, draw attention, and provide an understanding of the advancement......more
Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research d......more
This text explores the state-of-the-art in the rapidly developing theory of impulse control and introduces the theory of......more
This textbook is an introduction to nonlinear optimization, which treats mathematical concepts stringently on the one ha......more
This is a textbook that covers several selected topics in the theory of elliptic partial differential equations which ca......more
This is a textbook that covers several selected topics in the theory of elliptic partial differential equations which ca......more
The calculus of variations is one of the oldest subjects in mathematics, and it is very much alive and still evolving. B......more
The calculus of variations is one of the oldest subjects in mathematics, and it is very much alive and still evolving. B......more
This handbook aims to serve as a one-stop, reliable resource, including curated surveys and expository contributions on ......more
The model-based approach for carrying out classification and identification of tasks has led to the pervading progress o......more
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This book covers using R for doing optimization, a key area of operations research, which has been applied to virtually ......more
In this book Lukas Graf studies dynamic network flows which are a model for individual car traffic in road networks. It ......more
Optimization: 100 Examples is a book devoted to the analysis of scenarios for which the use of well-known optimization m......more
This contributed volume guides researchers and practitioners on resource collaborative management of supply chains and m......more
Introduction to Python: with Applications in Optimization, Image and Video Processing, and Machine Learning is intended ......more
Introduction to Python: with Applications in Optimization, Image and Video Processing, and Machine Learning is intended ......more
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