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Full-Text Articles in Computer Sciences
Elitist Schema Overlays: A Multi-Parent Genetic Operator, Nick Nichols, Mark Liffiton, Faculty Advisor
Elitist Schema Overlays: A Multi-Parent Genetic Operator, Nick Nichols, Mark Liffiton, Faculty Advisor
John Wesley Powell Student Research Conference
Genetic Algorithms are programs inspired by natural evolution used to solve difficult problems in Mathematics and Computer Science. The theoretical foundations of Genetic Algorithms, the schema theorem and the building-block hypothesis, state that the success of Genetic Algorithms stems from the propagation of fit genetic subsequences. Multi-parent operators were shown to increase the performance of Genetic Algorithms by increasing the disruptivity of genetic operations. Disruptive genetic operators help prevent suboptimal genetic sequences from propagating into future generations, which leads to an improved fitness for the population over time. In this paper we explore the use of a novel multi-parent genetic …
Liffiton Develops Free App For Teachers, Kim Hill
Liffiton Develops Free App For Teachers, Kim Hill
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Analyzing And Extending An Infeasibility Analysis Algorithm, Ammar Malik
Analyzing And Extending An Infeasibility Analysis Algorithm, Ammar Malik
Honors Projects
Constraint satisfaction problems (CSPs) involve finding assignments to a set of variables that satisfy some mathematical constraints. Unsatisfiable constraint problems are CSPs with no solution. However, useful characteristic subsets of these problems may be extracted with algorithms such as the MARCO algorithm, which outperforms the best known algorithms in the literature. A heuristic choice in the algorithm affects how it traverses the search space to output these subsets. This work analyzes the effect of this choice and introduces three improvements to the algorithm. The first of these improvements sacrifices completeness in terms of one type of subset in order to …