Browsing by Author "McMahon, Mathew T."

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    A Distributed Genetic Algorithm With Migration for the Design of Composite Laminate Structures
    McMahon, Mathew T. (Virginia Tech, 1998-08-05)
    This thesis describes the development of a general Fortran 90 framework for the solution of composite laminate design problems using a genetic algorithm (GA). The initial Fortran 90 module and package of operators result in a standard genetic algorithm (sGA). The sGA is extended to operate on a parallel processor, and a migration algorithm is introduced. These extensions result in the distributed genetic algorithm with migration (dGA). The performance of the dGA in terms of cost and reliability is studied and compared to an sGA baseline, using two types of composite laminate design problems. The nondeterminism of GAs and the migration and dynamic load balancing algorithm used in this work result in a changed (diminished) workload, so conventional measures of parallelizability are not meaningful. Thus, a set of experiments is devised to characterize the run time performance of the dGA. The migration algorithm is found to diminish the normalized cost and improve the reliability of a GA optimization run. An effective linear speedup for constant work is achieved, and the dynamic load balancing algorithm with distributed control and token ring termination detection yield improved run time performance.
  • A Distributed Genetic Algorithm with Migration for the Design of Composite Laminate Structures
    McMahon, Mathew T.; Watson, Layne T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1998-08-01)
    This paper describes the development of a general Fortran 90 framework for the solution of composite laminate design problems using a genetic algorithm (GA). The initial Fortran 90 module and package of operators result in a standard genetic algorithm (sGA). The sGA is extended to operate on a parallel processor, and a migration algorithm is introduced. These extensions result in the distributed genetic algorithm with migration (dGA). The performance of the dGA in terms of cost and reliability is studied and compared to a sGA baseline, using two types of composite laminate design problems. The nondeterminism of GAs and the migration and dynamic load balancing algorithm used in this work result in a changed (diminished) workload, so conventional measures of parallelizability are not meaningful. Thus, a set of experiments is devised to characterize the run time performance of the dGA.
  • A Fortran 90 Genetic Algorithm Module for Composite Laminate Structure Design
    McMahon, Mathew T.; Watson, Layne T.; Soremekun, G.A.; Gürdal, Zafer; Haftka, Raphael T. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1998-08-01)
    The design of the stacking sequence for a composite laminate involves a set of discrete variables (ply material and ply orientation), and is thus well-suited to genetic algorithms for design optimization. Such algorithms have typically been custom-designed in FORTRAN 77 to suit specific optimization problems. Fortran 90 is a modern, powerful language with features that support important programming concepts, including those used in object-oriented programming. The Fortran 90 genetic algorithm module is used to define genetic data types, the functions which use these data types, and to provide a general framework for solving composite laminate structure design problems. The language's support of abstract data types is used to build genetic structures such as populations, subpopulaions, individuals, chromosomes, and genes, and these data types are combined and manipulated by module subroutines. The use of abstract data types and long variable names makes the code useful and easily understood, while dynamic memory allocation makes the module flexible enough to be used in design problems of varying size and specification.