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Combinatorial, Linear, Integer and Nonlinear Optimization Apps

About Combinatorial, Linear, Integer and Nonlinear Optimization Apps

This textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN). Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and relatedmathematics.

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  • Language:
  • English
  • ISBN:
  • 9783030758035
  • Binding:
  • Paperback
  • Pages:
  • 284
  • Published:
  • October 18, 2022
  • Edition:
  • 22001
  • Dimensions:
  • 210x16x279 mm.
  • Weight:
  • 699 g.
Delivery: 2-4 weeks
Expected delivery: January 25, 2025
Extended return policy to January 30, 2025
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Description of Combinatorial, Linear, Integer and Nonlinear Optimization Apps

This textbook provides an introduction to the use and understanding of optimization and modeling for upper-level undergraduate students in engineering and mathematics. The formulation of optimization problems is founded through concepts and techniques from operations research: Combinatorial Optimization, Linear Programming, and Integer and Nonlinear Programming (COLIN). Computer Science (CS) is also relevant and important given the applications of algorithms and Apps/algorithms (A) in solving optimization problems. Each chapter provides an overview of the main concepts of optimization according to COLINA, providing examples through App Inventor and AMPL software applications. All apps developed through the text are available for download. Additionally, the text includes links to the University of Wisconsin NEOS server, designed to handle more computing-intensive problems in complex optimization. Readers are encouraged to have some background in calculus, linear algebra, and relatedmathematics.

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