Title page for ETD etd-05272008-153619


Type of Document Master's Thesis
Author Martz, Matthew
Author's Email Address mmartz@vt.edu
URN etd-05272008-153619
Title Preliminary Design of an Autonomous Underwater Vehicle Using a Multiple-Objective Genetic Optimizer
Degree Master of Science
Department Aerospace and Ocean Engineering
Advisory Committee
Advisor Name Title
Neu, Wayne L. Committee Chair
Brown, Alan J. Committee Member
Stilwell, Daniel J. Committee Member
Keywords
  • MDO
  • Optimization
  • Genetic
  • Genetic Algorithm
  • AUV
  • Autonomous Underwater Vehicle
Date of Defense 2008-05-27
Availability unrestricted
Abstract
The process developed herein uses a Multiple Objective Genetic Optimization (MOGO) algorithm. The optimization is implemented in ModelCenter (MC) from Phoenix Integration. It uses a genetic algorithm that searches the design space for optimal, feasible designs by considering three Measures of Performance (MOPs): Cost, Effectiveness, and Risk. The complete synthesis model is comprised of an input module, the three primary AUV synthesis modules, a constraint module, three objective modules, and a genetic algorithm. The effectiveness rating determined by the synthesis model is based on nine attributes identified in the US Navy’s UUV Master Plan and four performance-based attributes calculated by the synthesis model. To solve multi-attribute decision problems the Analytical Hierarchy Process (AHP) is used. Once the MOGO has generated a final generation of optimal, feasible designs the decision-maker(s) can choose candidate designs for further analysis. A sample AUV Synthesis was performed and five candidate AUVs were analyzed.
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