Pin Kung

Graduation Semester and Year

2012

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Victoria Chen

Abstract

Green building is a sustainable concept to reduce environmental impact. Decision–making for green building is a complex task. A multi–stage green building framework will guide future development of a comprehensive multiple stage, multiple objective (MSMO) decision–making framework. The software eQUEST is utilized in a design and analysis of computer experiments (DACE) approach to study building options that potentially impact energy usage and cost metrics. The DACE approach uses experimental design and statistical analysis to uncover multivariate patterns that will provide guidance for green building decisions. The computer experiments execute the green building software tools ATHENA [11] and eQUEST [13]. The experiment uses a Latin hypercube design to combine a mixed–level orthogonal array for discrete variables with a number–theoretic method for continuous variables. To accommodate the mix of discrete and continuous factor variables, the statistical analysis method fits treed regression (TreeReg) [51], TreeMARS [52], categorical TreeReg (CATreeReg) and categorical TreeMARS (CATreeMARS) models, and uses the method of seemingly unrelated regressions (SUR) [26], [27] to estimate the coefficients for a multiple response linear statistical model.

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

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