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The Quadratic Unconstrained Binary Optimization Problem: Theory, Algorithms, and Applications
The Quadratic Unconstrained Binary Optimization Problem: Theory, Algorithms, and Applications
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- More about The Quadratic Unconstrained Binary Optimization Problem: Theory, Algorithms, and Applications
The quadratic binary optimization problem (QUBO) is a versatile combinatorial optimization model with applications in finance, clustering, traffic management, machine scheduling, VLSI physical design, physics, quantum computing, engineering, and medicine. This book provides a comprehensive treatment of QUBO, including theory, algorithms, and applications, with a focus on modelling, complexity, and polynomially solvable special cases, exact and heuristic algorithms, approximation algorithms, metaheuristics, polyhedral structure, probabilistic analysis, persistencies, and related topics.
Format: Hardback
Length: 319 pages
Publication date: 13 July 2022
Publisher: Springer International Publishing AG
The quadratic binary optimization problem (QUBO) is a highly versatile combinatorial optimization model that finds applications across a wide range of fields. Its theoretical foundations are robust, making it a valuable tool for solving complex problems. QUBO has found use in finance, cluster analysis, traffic management, machine scheduling, VLSI physical design, physics, quantum computing, engineering, and medicine, among others. Moreover, various mathematical optimization problems can be rephrased as QUBO, including the resource constrained assignment problem, set partitioning problem, maximum cut problem, quadratic assignment problem, the bipartite unconstrained binary optimization problem, and more.
This book aims to provide a comprehensive and systematic development of theory, algorithms, and applications of QUBO. It offers a comprehensive treatment of the topic, covering various perspectives such as historical introduction, applications modeling, complexity analysis, polynomially solvable special cases, exact and heuristic algorithms, approximation algorithms, metaheuristics, polyhedral structure, probabilistic analysis, persistencies, and related topics. Additionally, available software for solving QUBO is introduced, encompassing public domain, commercial, and quantum computing-based codes.
By exploring the rich theoretical properties and diverse applications of QUBO, this book serves as a valuable resource for researchers, practitioners, and students in the fields of optimization, mathematics, and computer science. It provides a solid foundation for further research and development in this exciting and rapidly evolving area.
Weight: 670g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031045196
Edition number: 1st ed. 2022
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