Combinatorial, Linear, Integer and Nonlinear Optimization Apps
Description
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 related mathematics.
Reviews / Votes
"Throughout the book and the problems considered, the problem description is presented first, followed by a mathematical model, a solution algorithm and app, and a final evaluation. The layout of the book is easy to follow with many independent chunks that can be recorded during teaching if needed." (Efstratios Rappos, zbMATH 1492.90082, 2022)"Throughout the book and the problems considered, the problem description is presented first, followed by a mathematical model, a solution algorithm and app, and a final evaluation. The layout of the book is easy to follow with many independent chunks that can be recorded during teaching if needed." (Efstratios Rappos, zbMATH 1492.90082, 2022)
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Professor Smith has a Ph.D. in Mechanical and Industrial Engineering (MIE) from the University of Illinois, Champaign-Urbana. He is currently a full professor in the MIE Department at the University of Massachusetts, Amherst. His research concerns performance modeling of stochastic and deterministic networks. His experience in teaching optimization laid the foundation for this COLINA Volume.