Worcester Polytechnic Institute Electronic Theses and Dissertations Collection

Title page for ETD etd-050306-211907


Document Typethesis
Author NameZhou, Yao
URNetd-050306-211907
TitleStudy on Genetic Algorithm Improvement and Application
DegreeMS
DepartmentManufacturing Engineering
Advisors
  • Yiming(Kevin) Rong, Advisor
  • Diran Apelian, Committee Member
  • Richard Sisson, Committee Member
  • Keywords
  • tolerance assignment
  • genetic algorithms
  • Date of Presentation/Defense2006-05-01
    Availability unrestricted

    Abstract

    Genetic Algorithms (GAs) are powerful tools to solve large scale design optimization problems. The research interests in GAs lie in both its theory and application. On one hand, various modifications have been made on early GAs to allow them to solve problems faster, more accurately and more reliably. On the other hand, GA is used to solve complicated design optimization problems in different applications.

    The study in this thesis is both theoretical and applied in nature. On the theoretical side, an improved GA—Evolution Direction Guided GA (EDG-GA) is proposed based on the analysis of Schema Theory and Building Block Hypothesis. In addition, a method is developed to study the structure of GA solution space by characterizing interactions between genes. This method is further used to determine crossover points for selective crossover. On the application side, GA is applied to generate optimal tolerance assignment plans for a series of manufacturing processes. It is shown that the optimal tolerance assignment plan achieved by GA is better than that achieved by other optimization methods such as sensitivity analysis, given comparable computation time.

    Files
  • yzhou.pdf

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