DuPont, B., & Hoyle, C. (2015, June), Automation and Optimization of Engineering Design Team Selection Considering Personality Types and Course-Specific Constraints  Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23612

\bibitem{asee_peer_23612}
  DuPont, B., \& Hoyle, C. (2015, June), \emph{Automation and Optimization of Engineering Design Team Selection Considering Personality Types and Course-Specific Constraints}
  Paper presented at 2015 ASEE Annual Conference \& Exposition, Seattle, Washington.
  10.18260/p.23612

Bryony DuPont and Christopher Hoyle.  "Automation and Optimization of Engineering Design Team Selection Considering Personality Types and Course-Specific Constraints".  2015 ASEE Annual Conference & Exposition, Seattle, Washington, 2015, June.  ASEE Conferences, 2015.  https://strategy.asee.org/23612 Internet.  14 May, 2024

\bibitem{asee_peer_23612}
  Bryony DuPont and Christopher Hoyle.
  "Automation and Optimization of Engineering Design Team Selection Considering Personality Types and Course-Specific Constraints".
  \emph{2015 ASEE Annual Conference \& Exposition, Seattle, Washington, 2015, June}.
  ASEE Conferences, 2015.
  https://strategy.asee.org/23612 Internet.  14 May, 2024

@INPROCEEDINGS{asee_peer_23612
author = "Bryony DuPont and Christopher Hoyle"
title = "Automation and Optimization of Engineering Design Team Selection Considering Personality Types and Course-Specific Constraints"
booktitle = "2015 ASEE Annual Conference \& Exposition"
year = "2015"
month = "June"
address = "Seattle, Washington"
publisher = "ASEE Conferences"
note = {https://strategy.asee.org/23612}
number = {10.18260/p.23612}
}

TY  - CPAPER
AB  -           THE DESIGN TEAM OPTIMIZER: Automating the Selection            of Successful Design Teams Considering Personality Type                             and Project Preference     is home to one of the largest mechanical engineering designgroups in the US, which has been a leader in undergraduate design education. The undergraduatedesign sequence includes a junior-level introductory course and a multi-term senior-levelcapstone course. In the introductory course, students have been placed on design teamsconsidering MBTI personality types for more than twenty years; however, the instructor hasalways performed this team selection process manually. Similarly, in the senior capstone course,students are introduced to a breadth of available research or industry-sponsored projects, andthen are manually placed on teams depending on students’ ranking of their interest in eachproject, as well as their MBTI characteristics.    Optimal team selection in introductory and capstone mechanical design courses is vital to thesuccess of the project, and as such, many studies have been conducted to determine the means ofgenerating ideal design teams. This work seeks to employ multiple areas of design team theory,including the use of Myers-Briggs Type Indicators (MBTI) for personality assessment and thecapability for students to be placed in teams with respect to their preference for certain availableprojects, in order to automate the optimization of design team selection. Various test cases areshown that indicate the weighted multi-objective Mixed-Integer Linear Programming approachshown can quickly select optimal design teams that consist of diverse personality types andassign students to preferred projects. This work serves as the first step toward a web-basedautomated design team selection tool that will be made freely available to design researchers andeducators.
AU  - Bryony DuPont
AU  - Christopher Hoyle
CY  - Seattle, Washington
DA  - 2015/06/14
PB  - ASEE Conferences
TI  - Automation and Optimization of Engineering Design Team Selection Considering Personality Types and Course-Specific Constraints
UR  - https://strategy.asee.org/23612
DO  - 10.18260/p.23612
ER  -