Nonlinear regression is a form of regression analysis in which data is fit to a model and then expressed as a mathematical function. Simple linear regression relates two variables (X and Y) with a ...

Linear and Nonlinear Programming by Leunberger and Ye, Springer, 2008 (find ebook from CU Library website) Numerical Optimization, Nocedal and Wright, Springer, 2006 (find ebook from CU Library ...

Studies linear and nonlinear programming, the simplex method, duality, sensitivity, transportation and network flow problems, some constrained and unconstrained optimization theory, and the ...

Introduction to theory and the solution of linear and nonlinear programming problems: including linear programming, duality, the simplex method, lagrangian duality, convex programming and KKT ...

The equation y = x is linear because adding together inputs yields the sum of their respective outputs: 1 = 1, 2 = 2, and 1 + 2 = 1 + 2. But that’s not true of y = x 2: if x is 1, y is 1; if x ...

OR406.1 Foundations of Mathematical Programming: An introduction to the mathematical foundations of mathematical programming OR406.2 Mathematical Programming: Introduction to theory and the solution ...

Eventually linear programming came to be used in everything from manufacturing to diet planning. George Bernard Dantzig was born in Portland, Ore., on Nov. 8, 1914.