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Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms, Karl R. Deerman
Protein Structure Prediction Using Parallel Linkage Investigating Genetic Algorithms, Karl R. Deerman
Theses and Dissertations
AFIT has had a long-standing interest in solving the protein structure prediction (PSP) problem. The PSP problem is an intractable problem that if "solved" can lead to revolutionary new techniques for everything from the development of new medicines to optical computer switches. The challenge is to find a reliable and consistent method of predicting the 3-dimensional structure of a protein given its defining sequence of amino acids. PSP is primarily concerned with predicting the tertiary protein structure without regards to how the protein came to this folded state. The tertiary structure determines the protein's functionality.
A Comparison Of Genetic Algorithm Parametrization On Synthetic Optimization Problems, Mehmet Eravsar
A Comparison Of Genetic Algorithm Parametrization On Synthetic Optimization Problems, Mehmet Eravsar
Theses and Dissertations
Meta-heuristics have been deployed to solve many hard combinatorial and optimization problems. Parameterization of meta-heuristics is an important challenging aspect of meta-heuristic use since many of the features of these algorithms cannot be explained theoretically. Experiences with Genetic Algorithms (GA) applied to Multidimensional Knapsack Problems (MKP) have shown that this class of algorithm is very sensitive to parameterization. Many studies use standard test problems, which provide a firm basis for study comparisons but ignore the effect of problem correlation structure. This thesis applies GA to MKP. A new random repair operator, which projects infeasible solutions into feasible region, is proposed. …