This thesis deals with a modification to an existing mathematical
ppogramming algorithm called Beale's method. This method is
designed to solve only quadratic or linear programming problems.
The modification proposed aims to solve some of the problems this
method encounters and to shorten the time required for solution by
examining...
The objective of this thesis is to develop and
computationally test a new algorithm for the class of
network models with generalized upper bound (GUB) side
constraints. Various algorithms have been developed to
solve the network with arbitrary side constraints problem;
however, no algorithm that exploits the special structure
of...
Support Vector Machines (SVM) and Random Forests (RF) have
consistently outperformed other machine learning algorithms on a variety of
problems. SVM can be used for classification and regression on many types of
data (e.g. nonlinear, high dimensional), but cannot handle missing or mixed data.
This research implements a permutation-based variable...
Alteration of natural areas in attempts to support increasing human populations has been a crucial yet less publicized contributor to the fall of many of the world's greatest civilizations, since healthy ecosystems can help maintain stable societies and economies. Given this unhappy fact and the ancient relationship between people and...
This paper presents a framework for analyzing efficient spatial allocation of forest
management efforts - fuel treatment and harvest - under the risk of fire. The framework
integrates a fire behavior model and a spatially-explicit stochastic dynamic optimization
model. I investigate the effects of spatial interaction across plots during forest...
