Award Date
August 2017
Degree Type
Thesis
Degree Name
Master of Science in Engineering (MSE)
Department
Civil and Environmental Engineering and Construction
First Committee Member
Alexander Paz
Second Committee Member
Mohamed Kaseko
Third Committee Member
Dave James
Fourth Committee Member
Brendan Morris
Fifth Committee Member
Justin Zhan
Number of Pages
55
Abstract
Mixed logit models are a widely-used tool for studying discrete outcome problems. Modeling development entails answering three important questions that highly affect the quality of the specification: (i) what variables are considered in the analysis? (ii) what are going to be the coefficients for these variables? and (iii) what density function these coefficients will follow? The literature provides guidance; however, a strong statistical background and an ad hoc search process are required to obtain the best model specification. Knowledge of the problem context and data is required. Given a dataset including discrete outcomes and associated characteristics the problem to be addressed in this thesis is to investigate to what extend a relatively simple metaheuristic such as Simulated Annealing, can determine the best model specification for a mixed logit model and answer the above questions. A mathematical programing formulation is proposed and simulated annealing is implemented to find solutions for the proposed formulation. Three experiments were performed to test the effectiveness of the proposed algorithm. A comparison with existing model specifications for the same datasets was performed. The results suggest that the proposed algorithm is able to find an adequate model specification in terms of goodness of fit thereby reducing involvement of the analyst.
Keywords
Discrete Outcome; Mixed Logit; Optimization
Disciplines
Economics | Engineering
File Format
Degree Grantor
University of Nevada, Las Vegas
Language
English
Repository Citation
Arteaga Sanchez, Cristian David, "Specification of Mixed Logit Models Using an Optimization Approach" (2017). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3068.
http://dx.doi.org/10.34917/11156697
Rights
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