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ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
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PRIB'07 Proceedings of the 2nd IAPR international conference on Pattern recognition in bioinformatics
Efficient computation of fitness function by pruning in hydrophobic-hydrophilic model
ISBMDA'05 Proceedings of the 6th International conference on Biological and Medical Data Analysis
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EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
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This paper presents the impact of twins and the measures for their removal from the population of genetic algorithm (GA) when applied to effective conformational searching. It is conclusively shown that a twin removal strategy for a GA provides considerably enhanced performance when investigating solutions to complex ab initio protein structure prediction (PSP) problems in low-resolution model. Without twin removal, GA crossover and mutation operations can become ineffectual as generations lose their ability to produce significant differences, which can lead to the solution stalling. The paper relaxes the definition of chromosomal twins in the removal strategy to not only encompass identical, but also highly correlated chromosomes within the GA population, with empirical results consistently exhibiting significant improvements solving PSP problems.