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Physical Sciences and Mathematics Commons

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Air Force Institute of Technology

2005

Genetic algorithms

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Full-Text Articles in Physical Sciences and Mathematics

Explicit Building Block Multiobjective Evolutionary Computation: Methods And Applications, Richard O. Day Jun 2005

Explicit Building Block Multiobjective Evolutionary Computation: Methods And Applications, Richard O. Day

Theses and Dissertations

This dissertation presents principles, techniques, and performance of evolutionary computation optimization methods. Concentration is on concepts, design formulation, and prescription for multiobjective problem solving and explicit building block (BB) multiobjective evolutionary algorithms (MOEAs). Current state-of-the-art explicit BB MOEAs are addressed in the innovative design, execution, and testing of a new multiobjective explicit BB MOEA. Evolutionary computation concepts examined are algorithm convergence, population diversity and sizing, genotype and phenotype partitioning, archiving, BB concepts, parallel evolutionary algorithm (EA) models, robustness, visualization of evolutionary process, and performance in terms of effectiveness and efficiency. The main result of this research is the development of …


A Genetic Algorithm For Uav Routing Integrated With A Parallel Swarm Simulation, Matthew A. Russell Mar 2005

A Genetic Algorithm For Uav Routing Integrated With A Parallel Swarm Simulation, Matthew A. Russell

Theses and Dissertations

This research investigation addresses the problem of routing and simulating swarms of UAVs. Sorties are modeled as instantiations of the NP-Complete Vehicle Routing Problem, and this work uses genetic algorithms (GAs) to provide a fast and robust algorithm for a priori and dynamic routing applications. Swarms of UAVs are modeled based on extensions of Reynolds' swarm research and are simulated on a Beowulf cluster as a parallel computing application using the Synchronous Environment for Emulation and Discrete Event Simulation (SPEEDES). In a test suite, standard measures such as benchmark problems, best published results, and parallel metrics are used as performance …