Learning structure in nested logit models

• Main Author: Aboutaleb, Youssef Medhat.
• Other Authors: Moshe Ben-Akiva and Patrick Jaillet.
• Format: Others
• Language: English
• Published: Massachusetts Institute of Technology 2019
• Subjects: Civil and Environmental Engineering.; Electrical Engineering and Computer Science.
• Online Access: https://hdl.handle.net/1721.1/123208

This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. === Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019 === Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 === Cataloged from student-submitted PDF version of thesis. === Includes bibliographical references (pages 67-68). === This work is about developing an estimation procedure for nested logit models that optimizes over the nesting structure in addition to the model parameters. Current estimation practices require an a priori specification of a nesting structure. We formulate the problem of learning an optimal nesting structure as a mixed integer nonlinear programming (MINLP) optimization problem and solve it using a variant of the linear outer approximation algorithm. We demonstrate that it is indeed possible to recover the nesting structure directly from the data by applying our method to synthetic and real datasets. === by Youssef Medhat Aboutaleb. === S.M. in Transportation === S.M. === S.M.inTransportation Massachusetts Institute of Technology, Department of Civil and Environmental Engineering === S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science