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Linear and Nonlinear Programming with Maple

Paul E. Fishback
€235.60
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advanced mathematical programming techniques
Alternative Optimal Solutions
Author_Paul E. Fishback
basic
Basic Feasible Solution
Category=PBF
Cutting Plane Algorithm
decision
Decision Variable
Dual LP
Dual Simplex Algorithm
eigenvalue analysis
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Equilibrium Mixed Strategy
feasible
function
KKT Point
Linear Independent Vectors
Matrix Inequality Form
matrix partitioning
Minimum Cost Network Flow Problem
Mixed Strategy Nash Equilibrium
Multiple Linear Regression
Multiplier Vectors
Nonbasic Variables
objective
optimization theory
Original LP
Reduced Row Echelon Form
region
Row Echelon Form
S1 S2
S1 S2 S3
sensitivity analysis
Simplex Algorithm
slack
Slack Variable
solution
spectral theorem applications
Steepest Descent Method
unconstrained optimization
variable
variables
X1 X2 S1 S2
X2 S1 S2 S3 S4

Product details

  • ISBN 9781420090642
  • Weight: 703g
  • Dimensions: 156 x 234mm
  • Publication Date: 09 Dec 2009
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Description

Helps Students Understand Mathematical Programming Principles and Solve Real-World Applications

Supplies enough mathematical rigor yet accessible enough for undergraduatesIntegrating a hands-on learning approach, a strong linear algebra focus, Maple™ software, and real-world applications, Linear and Nonlinear Programming with Maple™: An Interactive, Applications-Based Approach introduces undergraduate students to the mathematical concepts and principles underlying linear and nonlinear programming. This text fills the gap between management science books lacking mathematical detail and rigor and graduate-level books on mathematical programming.

Essential linear algebra tools
Throughout the text, topics from a first linear algebra course, such as the invertible matrix theorem, linear independence, transpose properties, and eigenvalues, play a prominent role in the discussion. The book emphasizes partitioned matrices and uses them to describe the simplex algorithm in terms of matrix multiplication. This perspective leads to streamlined approaches for constructing the revised simplex method, developing duality theory, and approaching the process of sensitivity analysis. The book also discusses some intermediate linear algebra topics, including the spectral theorem and matrix norms.

Maple enhances conceptual understanding and helps tackle problems
Assuming no prior experience with Maple, the author provides a sufficient amount of instruction for students unfamiliar with the software. He also includes a summary of Maple commands as well as Maple worksheets in the text and online. By using Maple’s symbolic computing components, numeric capabilities, graphical versatility, and intuitive programming structures, students will acquire a deep conceptual understanding of major mathematical programming principles, along with the ability to solve moderately sized rea
About Paul E. Fishback

Paul E. Fishback is a professor in the Department of Mathematics at Grand Valley State University in Allendale, Michigan, USA.

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