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Linear and Integer Programming Made Easy [electronic resource] / by T. C. Hu, Andrew B. Kahng.

By: Hu, T. C [author.].
Contributor(s): Kahng, Andrew B [author.] | SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: X, 143 p. 24 illus., 1 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319240015.Subject(s): Electronic circuits | Computer science—Mathematics | Engineering mathematics | Engineering—Data processing | Mathematics | Electronic Circuits and Systems | Mathematical Applications in Computer Science | Mathematical and Computational Engineering Applications | Applications of MathematicsAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.3815 Online resources: Click here to access online
Contents:
Preliminaries -- Introduction -- Dimension of the Solution Space -- Introduction to the Simplex Method -- Duality and Complementary Slackness -- Revised Simplex Method -- Column Generating Technique -- The Knapsack Problem -- Asymptotic Algorithms -- The World Map of Integer Programs -- Linear and Integer Programming in Practice.
In: Springer Nature eBookSummary: Linear and integer programming are fundamental toolkits for data and information science and technology, particularly in the context of today’s megatrends toward statistical optimization, machine learning, and big data analytics. Drawn from over 30 years of classroom teaching and applied research experience, this textbook provides a crisp and practical introduction to the basics of linear and integer programming. The authors’ approach is accessible to students from all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification, and computer vision. Readers will learn to cast hard combinatorial problems as mathematical programming optimizations, understand how to achieve formulations where the objective and constraints are linear, choose appropriate solution methods, and interpret results appropriately. •Provides a concise introduction to linear and integer programming, appropriate for undergraduates, graduates, a short course or boot camp, or self-learning; •Targets not only computer scientists and engineers, but those in management science and operations research as well; •Emphasizes basics and intuitive concepts, and gives corresponding numerical examples; •Includes exercises to test and reinforce the concepts introduced, along with a website containing additional material matched to the book’s contents.
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Preliminaries -- Introduction -- Dimension of the Solution Space -- Introduction to the Simplex Method -- Duality and Complementary Slackness -- Revised Simplex Method -- Column Generating Technique -- The Knapsack Problem -- Asymptotic Algorithms -- The World Map of Integer Programs -- Linear and Integer Programming in Practice.

Linear and integer programming are fundamental toolkits for data and information science and technology, particularly in the context of today’s megatrends toward statistical optimization, machine learning, and big data analytics. Drawn from over 30 years of classroom teaching and applied research experience, this textbook provides a crisp and practical introduction to the basics of linear and integer programming. The authors’ approach is accessible to students from all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification, and computer vision. Readers will learn to cast hard combinatorial problems as mathematical programming optimizations, understand how to achieve formulations where the objective and constraints are linear, choose appropriate solution methods, and interpret results appropriately. •Provides a concise introduction to linear and integer programming, appropriate for undergraduates, graduates, a short course or boot camp, or self-learning; •Targets not only computer scientists and engineers, but those in management science and operations research as well; •Emphasizes basics and intuitive concepts, and gives corresponding numerical examples; •Includes exercises to test and reinforce the concepts introduced, along with a website containing additional material matched to the book’s contents.

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