Fundamentals of object oriented programming
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MIE250: Fundamentals of object oriented programming
1 Overview
In the previous projects, we built a nice framework for testing parameter variations in the steepest descent
algorithm. In this project, we will expand the framework to also examine how different line searches affect the
performance of our algorithm. The remainder of this section summarizes the description of the polynomial
functions and steepest descent algorithm from the previous project.
1.1 Polynomials
In this project, we will try to minimize polynomials of the form SimplePolynomialSum:
f(x1, . . . , xn) =
n
X
j=1
• Final objective function value
• Closeness to local minimum (` 2 norm of the gradient at the final solution)
• Number of iterations needed for the algorithm to run
• Computation time needed for the algorithm to run
1.2 The steepest descent algorithm
The steepest descent algorithm is part of a class of algorithms called directional search methods. Basically,
we start at some feasible point, pick a direction to move, pick an distance to move in the direction, and then
move to a new point by a taking a step along the selected distance. We repeat the process over and over
until we have reached some stopping criteria.