The quadratic unconstrained binary optimization problem : theory, algorithms, and applications / Abraham P. Punnen, editor.

"The quadratic binary optimization problem (QUBO) is a versatile combinatorial optimization model with a variety of applications and rich theoretical properties. Application areas of the model include finance, cluster analysis, traffic management, machine scheduling, VLSI physical design, physi...

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Bibliographic Details
Other Authors: Punnen, Abraham P. (Editor)
Format: eBook
Language:English
Published: Cham : Springer, [2022]
Subjects:
Online Access:Click for online access
Description
Summary:"The quadratic binary optimization problem (QUBO) is a versatile combinatorial optimization model with a variety of applications and rich theoretical properties. Application areas of the model include finance, cluster analysis, traffic management, machine scheduling, VLSI physical design, physics, quantum computing, engineering, and medicine. In addition, various mathematical optimization models can be reformulated as a QUBO, including the resource constrained assignment problem, set partitioning problem, maximum cut problem, quadratic assignment problem, the bipartite unconstrained binary optimization problem, among others. This book presents a systematic development of theory, algorithms, and applications of QUBO. It offers a comprehensive treatment of QUBO from various viewpoints, including a historical introduction along with an in-depth discussion of applications modelling, complexity and polynomially solvable special cases, exact and heuristic algorithms, analysis of approximation algorithms, metaheuristics, polyhedral structure, probabilistic analysis, persistencies, and related topics. Available software for solving QUBO is also introduced, including public domain, commercial, as well as quantum computing based codes."--
Physical Description:1 online resource (xiii, 319 pages) : illustrations (black and white, and colour)
Bibliography:Includes bibliographical references and index.
ISBN:9783031045202
3031045203
Source of Description, Etc. Note:Online resource; title from PDF title page (SpringerLink, viewed July 26, 2022).