Description: Basics of numerical optimization: problem formulation, conditions of optimality, search direction and step length. Calculus-based techniques for univariate and multivariate optimization.

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...

Purdue faculty dedicate countless hours to exploring the frontiers of their respective fields, pushing the boundaries of knowledge and contributing to the ever-evolving landscape of academia. To ...

In this paper the generalized Newton's method for LC¹ unconstrained optimization is investigated. This method is an extension of Newton's method for the smooth optimization. Some basic concepts are ...

Problem definition: Assortment selection is one of the most important decisions faced by retailers. Most existing papers in the literature assume that customers select at most one item out of the ...