Introduction Mathematical Programming Network by Grieve Nathan (19 results)
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Hardback. Condition: New. This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical techniques fr…om nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures.
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Hardback. Condition: New. This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical techniques fr…om nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures.
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Hardcover. Condition: new. Hardcover. This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical t…echniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Hardcover. Condition: new. Hardcover. This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical t…echniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Hardback. Condition: New. This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical techniques fr…om nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures.
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simp…lex Method in Python, and classical techniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures.
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Hardcover. Condition: new. Hardcover. This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation of the Simplex Method in Python, and classical t…echniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Language: English
Published by Springer Nature Switzerland AG Mai 2026, 2026
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementa…tion of the Simplex Method in Python, and classical techniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures. 322 pp. Englisch.
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Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This text provides a practical, hands-on introduction to the fundamental concepts of mathematical programming and network science. Particular emphasis is placed on linear programming, mathematical modelling and case studies, the implementation… of the Simplex Method in Python, and classical techniques from nonlinear convex programming. The text also features a discussion of mathematical programming within the context of algebraic modelling languages. Further, it includes material on matrix games, decision analysis, multicriteria optimization and non-directed networks. Designed as an introductory resource for upper-level undergraduate and graduate students, the book assumes only a modest mathematical background. Readers who have completed a second course in linear algebra, multivariable calculus, and an introductory course in probability and statistics will find the more advanced portions of the text especially accessible. Researchers and professionals in mathematics, engineering, technology, economics, business, and other quantitatively oriented fields will also find this book a valuable reference.A distinguishing feature of this text is its strong emphasis on case studies. Numerous examples are developed in detail, either worked out within the text or explored through exercises and abstract model formulations. This pedagogical approach fosters both intuition and a structured understanding of the representative models that form the foundation of the field. A rich collection of end-of-chapter exercises enables readers to apply concepts and deepen their mastery of the material. A chapter dependency chart further supports independent learners by suggesting an effective study sequence and assists instructors in organizing coherent course structures.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 344 pp. Englisch.
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Buch. Condition: Neu. An Introduction to Mathematical Programming and Network Science | Examples with Theory and Python | Nathan Grieve | Buch | Springer Undergraduate Texts in Mathematics and Technology | xix | Englisch | 2026 | Springer | EAN 9783032133298 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenst…r. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
