Which of the following is not one of the reasons an optimization model can become nonlinear
A) Nonconstant returns to scale.
B) The model objective is to minimize the sum of squared differences.
C) The model objective is a function of a variable times multiplied by a function of that same variable
D) The model objective is to minimize the sum of absolute errors.

Question

Which of the following is not one of the reasons an optimization model can become nonlinear
A) Nonconstant returns to scale. 
B) The model objective is to minimize the sum of squared differences. 
C) The model objective is a function of a variable times multiplied by a function of that same variable 
D) The model objective is to minimize the sum of absolute errors.

Quizplus · Accepted Answer

Nonlinearity in optimization models arises from factors such as nonconstant returns to scale, objectives involving squared differences (which introduce quadratic terms), and objectives that involve a variable multiplied by a function of itself, leading to non-linear relationships. Minimizing the sum of absolute errors, however, does not inherently make a model nonlinear, as it can be addressed through linear programming techniques by introducing auxiliary variables and constraints.

Which of the Following Is Not One of the Reasons