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Air Force Institute of Technology

2001

Genetic algorithms

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Traveling Salesman Problem For Surveillance Mission Using Particle Swarm Optimization, Barry R. Secrest Mar 2001

Traveling Salesman Problem For Surveillance Mission Using Particle Swarm Optimization, Barry R. Secrest

Theses and Dissertations

The surveillance mission requires aircraft to fly from a starting point through defended terrain to targets and return to a safe destination (usually the starting point). The process of selecting such a flight path is known as the Mission Route Planning (MRP) Problem and is a three-dimensional, multi-criteria (fuel expenditure, time required, risk taken, priority targeting, goals met, etc.) path search. Planning aircraft routes involves an elaborate search through numerous possibilities, which can severely task the resources of the system being used to compute the routes. Operational systems can take up to a day to arrive at a solution due …

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Implementation And Analysis Of The Parallel Genetic Rule And Classifier Construction Environment, David M. Strong Mar 2001

Implementation And Analysis Of The Parallel Genetic Rule And Classifier Construction Environment, David M. Strong

Theses and Dissertations

This paper discusses the Genetic Rule and Classifier Construction Environment (GRaCCE), which is an alternative to existing decision rule induction (DRI) algorithms. GRaCCE is a multi-phase algorithm which uses evolutionary search to mine classification rules from data. The current implementation uses a genetic algorithm based 0/1 search to reduce the number of features to a minimal set of features that make the most significant contributions to the classification of the input data set. This feature selection increases the efficiency of the rule induction algorithm that follows. However, feature selection is shown to account for more than 98 percent of the …

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