2016-17 Graduate Bulletin

After 2003 the University of Dayton Bulletin went exclusively online. This copy was downloaded from the University of Dayton\u27s website in March 2018.https://ecommons.udayton.edu/bulletin_grad/1047/thumbnail.jp

2017-18 Graduate Bulletin

After 2003 the University of Dayton Bulletin went exclusively online. This copy was downloaded from the University of Dayton\u27s website in March 2018.https://ecommons.udayton.edu/bulletin_grad/1048/thumbnail.jp

Perceptions and Evaluations of Assortment Variety

Given the explosive growth in the number of products, managing their assortments is a challenging task for retailers. An understanding of consumer responses to changes in assortment size and composition is required. This dissertation examines consumers' perceptions and evaluations of product assortments, with a focus on assortment variety. It investigates diverse measures of assortment variety, the influence of variety aspects on consumers' expectations of choice success and effort, and the combined influence of variety aspects, expertise, and preference awareness on store preference. In addition, a first exploration of consumers' product assortments, i.e. assortments that are owned by consumers, is provided.

Evolutionary Algorithms in Engineering Design Optimization

Evolutionary algorithms (EAs) are population-based global optimizers, which, due to their characteristics, have allowed us to solve, in a straightforward way, many real world optimization problems in the last three decades, particularly in engineering fields. Their main advantages are the following: they do not require any requisite to the objective/fitness evaluation function (continuity, derivability, convexity, etc.); they are not limited by the appearance of discrete and/or mixed variables or by the requirement of uncertainty quantification in the search. Moreover, they can deal with more than one objective function simultaneously through the use of evolutionary multi-objective optimization algorithms. This set of advantages, and the continuously increased computing capability of modern computers, has enhanced their application in research and industry. From the application point of view, in this Special Issue, all engineering fields are welcomed, such as aerospace and aeronautical, biomedical, civil, chemical and materials science, electronic and telecommunications, energy and electrical, manufacturing, logistics and transportation, mechanical, naval architecture, reliability, robotics, structural, etc. Within the EA field, the integration of innovative and improvement aspects in the algorithms for solving real world engineering design problems, in the abovementioned application fields, are welcomed and encouraged, such as the following: parallel EAs, surrogate modelling, hybridization with other optimization techniques, multi-objective and many-objective optimization, etc